├── 01-Variables.ipynb ├── 02-Strings.ipynb ├── 03-StringsAdvanced.ipynb ├── 04-Lists.ipynb ├── 05-Dictionary.ipynb ├── 06-Set.ipynb ├── 07-Tuple.ipynb ├── 08-Boolean.ipynb ├── 09-Exam 1.ipynb ├── 10-Exam 1 Solutions.ipynb ├── 11-Comparison.ipynb ├── 12-IfStatements.ipynb ├── 13-ForLoop.ipynb ├── 14-ContinueBreakPass.ipynb ├── 15-WhileLoop.ipynb ├── 16-UsefulMethods.ipynb ├── 17-MethodsAndFunctions.ipynb ├── 18-PracticalFunctions.ipynb ├── 19-Scope.ipynb ├── 20-Hangman.py ├── 21-Decorators.ipynb ├── 22-Calculator.py ├── 23-OOPClasses.ipynb ├── 24-SpecialMethods.ipynb ├── 25-ModulesPackages.ipynb ├── 26-yoda.py ├── 27-anakin.py ├── 28-ErrorHandling.ipynb ├── 33-MyFile.ipynb └── README.md /01-Variables.ipynb: -------------------------------------------------------------------------------- 1 | { 2 | "cells": [ 3 | { 4 | "cell_type": "code", 5 | "execution_count": 1, 6 | "metadata": {}, 7 | "outputs": [ 8 | { 9 | "data": { 10 | "text/plain": [ 11 | "11" 12 | ] 13 | }, 14 | "execution_count": 1, 15 | "metadata": {}, 16 | "output_type": "execute_result" 17 | } 18 | ], 19 | "source": [ 20 | "5+6" 21 | ] 22 | }, 23 | { 24 | "cell_type": "code", 25 | "execution_count": 2, 26 | "metadata": {}, 27 | "outputs": [ 28 | { 29 | "data": { 30 | "text/plain": [ 31 | "1994" 32 | ] 33 | }, 34 | "execution_count": 2, 35 | "metadata": {}, 36 | "output_type": "execute_result" 37 | } 38 | ], 39 | "source": [ 40 | "1500 + 494" 41 | ] 42 | }, 43 | { 44 | "cell_type": "code", 45 | "execution_count": 3, 46 | "metadata": {}, 47 | "outputs": [ 48 | { 49 | "data": { 50 | "text/plain": [ 51 | "128.57142857142858" 52 | ] 53 | }, 54 | "execution_count": 3, 55 | "metadata": {}, 56 | "output_type": "execute_result" 57 | } 58 | ], 59 | "source": [ 60 | "900/7" 61 | ] 62 | }, 63 | { 64 | "cell_type": "code", 65 | "execution_count": 4, 66 | "metadata": {}, 67 | "outputs": [ 68 | { 69 | "data": { 70 | "text/plain": [ 71 | "300" 72 | ] 73 | }, 74 | "execution_count": 4, 75 | "metadata": {}, 76 | "output_type": "execute_result" 77 | } 78 | ], 79 | "source": [ 80 | "500 - 200" 81 | ] 82 | }, 83 | { 84 | "cell_type": "code", 85 | "execution_count": 5, 86 | "metadata": {}, 87 | "outputs": [ 88 | { 89 | "data": { 90 | "text/plain": [ 91 | "120" 92 | ] 93 | }, 94 | "execution_count": 5, 95 | "metadata": {}, 96 | "output_type": "execute_result" 97 | } 98 | ], 99 | "source": [ 100 | "30 * 4" 101 | ] 102 | }, 103 | { 104 | "cell_type": "code", 105 | "execution_count": 6, 106 | "metadata": {}, 107 | "outputs": [ 108 | { 109 | "data": { 110 | "text/plain": [ 111 | "8" 112 | ] 113 | }, 114 | "execution_count": 6, 115 | "metadata": {}, 116 | "output_type": "execute_result" 117 | } 118 | ], 119 | "source": [ 120 | "2 * 2 * 2" 121 | ] 122 | }, 123 | { 124 | "cell_type": "code", 125 | "execution_count": 7, 126 | "metadata": {}, 127 | "outputs": [ 128 | { 129 | "data": { 130 | "text/plain": [ 131 | "8" 132 | ] 133 | }, 134 | "execution_count": 7, 135 | "metadata": {}, 136 | "output_type": "execute_result" 137 | } 138 | ], 139 | "source": [ 140 | "2 ** 3" 141 | ] 142 | }, 143 | { 144 | "cell_type": "code", 145 | "execution_count": 8, 146 | "metadata": {}, 147 | "outputs": [ 148 | { 149 | "data": { 150 | "text/plain": [ 151 | "512" 152 | ] 153 | }, 154 | "execution_count": 8, 155 | "metadata": {}, 156 | "output_type": "execute_result" 157 | } 158 | ], 159 | "source": [ 160 | "2**9" 161 | ] 162 | }, 163 | { 164 | "cell_type": "code", 165 | "execution_count": 9, 166 | "metadata": {}, 167 | "outputs": [ 168 | { 169 | "data": { 170 | "text/plain": [ 171 | "0" 172 | ] 173 | }, 174 | "execution_count": 9, 175 | "metadata": {}, 176 | "output_type": "execute_result" 177 | } 178 | ], 179 | "source": [ 180 | "10 % 2" 181 | ] 182 | }, 183 | { 184 | "cell_type": "code", 185 | "execution_count": 10, 186 | "metadata": {}, 187 | "outputs": [ 188 | { 189 | "data": { 190 | "text/plain": [ 191 | "1" 192 | ] 193 | }, 194 | "execution_count": 10, 195 | "metadata": {}, 196 | "output_type": "execute_result" 197 | } 198 | ], 199 | "source": [ 200 | "11%2" 201 | ] 202 | }, 203 | { 204 | "cell_type": "code", 205 | "execution_count": 11, 206 | "metadata": {}, 207 | "outputs": [ 208 | { 209 | "data": { 210 | "text/plain": [ 211 | "2" 212 | ] 213 | }, 214 | "execution_count": 11, 215 | "metadata": {}, 216 | "output_type": "execute_result" 217 | } 218 | ], 219 | "source": [ 220 | "11%3" 221 | ] 222 | }, 223 | { 224 | "cell_type": "code", 225 | "execution_count": 12, 226 | "metadata": {}, 227 | "outputs": [ 228 | { 229 | "data": { 230 | "text/plain": [ 231 | "1.5" 232 | ] 233 | }, 234 | "execution_count": 12, 235 | "metadata": {}, 236 | "output_type": "execute_result" 237 | } 238 | ], 239 | "source": [ 240 | "0.5 * 3" 241 | ] 242 | }, 243 | { 244 | "cell_type": "markdown", 245 | "metadata": {}, 246 | "source": [ 247 | "## Integer" 248 | ] 249 | }, 250 | { 251 | "cell_type": "code", 252 | "execution_count": 13, 253 | "metadata": {}, 254 | "outputs": [ 255 | { 256 | "data": { 257 | "text/plain": [ 258 | "6" 259 | ] 260 | }, 261 | "execution_count": 13, 262 | "metadata": {}, 263 | "output_type": "execute_result" 264 | } 265 | ], 266 | "source": [ 267 | "3 + 3" 268 | ] 269 | }, 270 | { 271 | "cell_type": "markdown", 272 | "metadata": {}, 273 | "source": [ 274 | "## Float" 275 | ] 276 | }, 277 | { 278 | "cell_type": "code", 279 | "execution_count": 14, 280 | "metadata": {}, 281 | "outputs": [ 282 | { 283 | "data": { 284 | "text/plain": [ 285 | "1.2000000000000002" 286 | ] 287 | }, 288 | "execution_count": 14, 289 | "metadata": {}, 290 | "output_type": "execute_result" 291 | } 292 | ], 293 | "source": [ 294 | "0.4 * 3.0" 295 | ] 296 | }, 297 | { 298 | "cell_type": "code", 299 | "execution_count": 15, 300 | "metadata": {}, 301 | "outputs": [ 302 | { 303 | "data": { 304 | "text/plain": [ 305 | "8" 306 | ] 307 | }, 308 | "execution_count": 15, 309 | "metadata": {}, 310 | "output_type": "execute_result" 311 | } 312 | ], 313 | "source": [ 314 | "3 + 5" 315 | ] 316 | }, 317 | { 318 | "cell_type": "markdown", 319 | "metadata": {}, 320 | "source": [ 321 | "## Variables" 322 | ] 323 | }, 324 | { 325 | "cell_type": "code", 326 | "execution_count": 16, 327 | "metadata": {}, 328 | "outputs": [], 329 | "source": [ 330 | "x = 3" 331 | ] 332 | }, 333 | { 334 | "cell_type": "code", 335 | "execution_count": 17, 336 | "metadata": {}, 337 | "outputs": [], 338 | "source": [ 339 | "y = 5" 340 | ] 341 | }, 342 | { 343 | "cell_type": "code", 344 | "execution_count": 18, 345 | "metadata": {}, 346 | "outputs": [ 347 | { 348 | "data": { 349 | "text/plain": [ 350 | "8" 351 | ] 352 | }, 353 | "execution_count": 18, 354 | "metadata": {}, 355 | "output_type": "execute_result" 356 | } 357 | ], 358 | "source": [ 359 | "x+y" 360 | ] 361 | }, 362 | { 363 | "cell_type": "code", 364 | "execution_count": 19, 365 | "metadata": {}, 366 | "outputs": [ 367 | { 368 | "data": { 369 | "text/plain": [ 370 | "243" 371 | ] 372 | }, 373 | "execution_count": 19, 374 | "metadata": {}, 375 | "output_type": "execute_result" 376 | } 377 | ], 378 | "source": [ 379 | "x**y" 380 | ] 381 | }, 382 | { 383 | "cell_type": "code", 384 | "execution_count": 20, 385 | "metadata": {}, 386 | "outputs": [], 387 | "source": [ 388 | "x = 4" 389 | ] 390 | }, 391 | { 392 | "cell_type": "code", 393 | "execution_count": 21, 394 | "metadata": {}, 395 | "outputs": [ 396 | { 397 | "data": { 398 | "text/plain": [ 399 | "9" 400 | ] 401 | }, 402 | "execution_count": 21, 403 | "metadata": {}, 404 | "output_type": "execute_result" 405 | } 406 | ], 407 | "source": [ 408 | "x+y" 409 | ] 410 | }, 411 | { 412 | "cell_type": "code", 413 | "execution_count": 22, 414 | "metadata": {}, 415 | "outputs": [ 416 | { 417 | "name": "stdout", 418 | "output_type": "stream", 419 | "text": [ 420 | "r: 5\n" 421 | ] 422 | } 423 | ], 424 | "source": [ 425 | "r = input(\"r: \")" 426 | ] 427 | }, 428 | { 429 | "cell_type": "code", 430 | "execution_count": 26, 431 | "metadata": {}, 432 | "outputs": [ 433 | { 434 | "data": { 435 | "text/plain": [ 436 | "int" 437 | ] 438 | }, 439 | "execution_count": 26, 440 | "metadata": {}, 441 | "output_type": "execute_result" 442 | } 443 | ], 444 | "source": [ 445 | "type(x)" 446 | ] 447 | }, 448 | { 449 | "cell_type": "code", 450 | "execution_count": 27, 451 | "metadata": {}, 452 | "outputs": [], 453 | "source": [ 454 | "pi = 3.14" 455 | ] 456 | }, 457 | { 458 | "cell_type": "code", 459 | "execution_count": 28, 460 | "metadata": {}, 461 | "outputs": [ 462 | { 463 | "data": { 464 | "text/plain": [ 465 | "float" 466 | ] 467 | }, 468 | "execution_count": 28, 469 | "metadata": {}, 470 | "output_type": "execute_result" 471 | } 472 | ], 473 | "source": [ 474 | "type(pi)" 475 | ] 476 | }, 477 | { 478 | "cell_type": "code", 479 | "execution_count": 29, 480 | "metadata": {}, 481 | "outputs": [ 482 | { 483 | "data": { 484 | "text/plain": [ 485 | "'5'" 486 | ] 487 | }, 488 | "execution_count": 29, 489 | "metadata": {}, 490 | "output_type": "execute_result" 491 | } 492 | ], 493 | "source": [ 494 | "r" 495 | ] 496 | }, 497 | { 498 | "cell_type": "code", 499 | "execution_count": 30, 500 | "metadata": {}, 501 | "outputs": [ 502 | { 503 | "data": { 504 | "text/plain": [ 505 | "str" 506 | ] 507 | }, 508 | "execution_count": 30, 509 | "metadata": {}, 510 | "output_type": "execute_result" 511 | } 512 | ], 513 | "source": [ 514 | "type(r)" 515 | ] 516 | }, 517 | { 518 | "cell_type": "code", 519 | "execution_count": 31, 520 | "metadata": {}, 521 | "outputs": [ 522 | { 523 | "data": { 524 | "text/plain": [ 525 | "12.56" 526 | ] 527 | }, 528 | "execution_count": 31, 529 | "metadata": {}, 530 | "output_type": "execute_result" 531 | } 532 | ], 533 | "source": [ 534 | "x * pi" 535 | ] 536 | }, 537 | { 538 | "cell_type": "code", 539 | "execution_count": 35, 540 | "metadata": {}, 541 | "outputs": [], 542 | "source": [ 543 | "r_int = int(r)" 544 | ] 545 | }, 546 | { 547 | "cell_type": "code", 548 | "execution_count": 36, 549 | "metadata": {}, 550 | "outputs": [ 551 | { 552 | "data": { 553 | "text/plain": [ 554 | "5" 555 | ] 556 | }, 557 | "execution_count": 36, 558 | "metadata": {}, 559 | "output_type": "execute_result" 560 | } 561 | ], 562 | "source": [ 563 | "r_int" 564 | ] 565 | }, 566 | { 567 | "cell_type": "code", 568 | "execution_count": 37, 569 | "metadata": {}, 570 | "outputs": [ 571 | { 572 | "data": { 573 | "text/plain": [ 574 | "int" 575 | ] 576 | }, 577 | "execution_count": 37, 578 | "metadata": {}, 579 | "output_type": "execute_result" 580 | } 581 | ], 582 | "source": [ 583 | "type(r_int)" 584 | ] 585 | }, 586 | { 587 | "cell_type": "code", 588 | "execution_count": 38, 589 | "metadata": {}, 590 | "outputs": [ 591 | { 592 | "data": { 593 | "text/plain": [ 594 | "31.400000000000002" 595 | ] 596 | }, 597 | "execution_count": 38, 598 | "metadata": {}, 599 | "output_type": "execute_result" 600 | } 601 | ], 602 | "source": [ 603 | "r_int * pi * 2" 604 | ] 605 | }, 606 | { 607 | "cell_type": "code", 608 | "execution_count": null, 609 | "metadata": {}, 610 | "outputs": [], 611 | "source": [] 612 | } 613 | ], 614 | "metadata": { 615 | "kernelspec": { 616 | "display_name": "Python 3", 617 | "language": "python", 618 | "name": "python3" 619 | }, 620 | "language_info": { 621 | "codemirror_mode": { 622 | "name": "ipython", 623 | "version": 3 624 | }, 625 | "file_extension": ".py", 626 | "mimetype": "text/x-python", 627 | "name": "python", 628 | "nbconvert_exporter": "python", 629 | "pygments_lexer": "ipython3", 630 | "version": "3.6.4" 631 | } 632 | }, 633 | "nbformat": 4, 634 | "nbformat_minor": 2 635 | } 636 | -------------------------------------------------------------------------------- /02-Strings.ipynb: -------------------------------------------------------------------------------- 1 | { 2 | "cells": [ 3 | { 4 | "cell_type": "code", 5 | "execution_count": 1, 6 | "metadata": {}, 7 | "outputs": [ 8 | { 9 | "data": { 10 | "text/plain": [ 11 | "'hello world'" 12 | ] 13 | }, 14 | "execution_count": 1, 15 | "metadata": {}, 16 | "output_type": "execute_result" 17 | } 18 | ], 19 | "source": [ 20 | "\"hello world\"" 21 | ] 22 | }, 23 | { 24 | "cell_type": "code", 25 | "execution_count": 2, 26 | "metadata": {}, 27 | "outputs": [ 28 | { 29 | "data": { 30 | "text/plain": [ 31 | "'hello'" 32 | ] 33 | }, 34 | "execution_count": 2, 35 | "metadata": {}, 36 | "output_type": "execute_result" 37 | } 38 | ], 39 | "source": [ 40 | "'hello'" 41 | ] 42 | }, 43 | { 44 | "cell_type": "code", 45 | "execution_count": 6, 46 | "metadata": {}, 47 | "outputs": [ 48 | { 49 | "data": { 50 | "text/plain": [ 51 | "\"i'm a pilot\"" 52 | ] 53 | }, 54 | "execution_count": 6, 55 | "metadata": {}, 56 | "output_type": "execute_result" 57 | } 58 | ], 59 | "source": [ 60 | "\"i'm a pilot\"" 61 | ] 62 | }, 63 | { 64 | "cell_type": "code", 65 | "execution_count": 7, 66 | "metadata": {}, 67 | "outputs": [], 68 | "source": [ 69 | "x = \"hello world\"" 70 | ] 71 | }, 72 | { 73 | "cell_type": "code", 74 | "execution_count": 8, 75 | "metadata": {}, 76 | "outputs": [ 77 | { 78 | "data": { 79 | "text/plain": [ 80 | "'hello world'" 81 | ] 82 | }, 83 | "execution_count": 8, 84 | "metadata": {}, 85 | "output_type": "execute_result" 86 | } 87 | ], 88 | "source": [ 89 | "x" 90 | ] 91 | }, 92 | { 93 | "cell_type": "code", 94 | "execution_count": 9, 95 | "metadata": {}, 96 | "outputs": [], 97 | "source": [ 98 | "x = \"hello\"" 99 | ] 100 | }, 101 | { 102 | "cell_type": "code", 103 | "execution_count": 10, 104 | "metadata": {}, 105 | "outputs": [ 106 | { 107 | "data": { 108 | "text/plain": [ 109 | "'hello'" 110 | ] 111 | }, 112 | "execution_count": 10, 113 | "metadata": {}, 114 | "output_type": "execute_result" 115 | } 116 | ], 117 | "source": [ 118 | "x" 119 | ] 120 | }, 121 | { 122 | "cell_type": "code", 123 | "execution_count": 11, 124 | "metadata": {}, 125 | "outputs": [], 126 | "source": [ 127 | "x = 3" 128 | ] 129 | }, 130 | { 131 | "cell_type": "code", 132 | "execution_count": 12, 133 | "metadata": {}, 134 | "outputs": [ 135 | { 136 | "data": { 137 | "text/plain": [ 138 | "3" 139 | ] 140 | }, 141 | "execution_count": 12, 142 | "metadata": {}, 143 | "output_type": "execute_result" 144 | } 145 | ], 146 | "source": [ 147 | "x" 148 | ] 149 | }, 150 | { 151 | "cell_type": "code", 152 | "execution_count": 13, 153 | "metadata": {}, 154 | "outputs": [], 155 | "source": [ 156 | "x = \"hello world\"" 157 | ] 158 | }, 159 | { 160 | "cell_type": "code", 161 | "execution_count": 14, 162 | "metadata": {}, 163 | "outputs": [ 164 | { 165 | "data": { 166 | "text/plain": [ 167 | "str" 168 | ] 169 | }, 170 | "execution_count": 14, 171 | "metadata": {}, 172 | "output_type": "execute_result" 173 | } 174 | ], 175 | "source": [ 176 | "type(x)" 177 | ] 178 | }, 179 | { 180 | "cell_type": "code", 181 | "execution_count": 15, 182 | "metadata": {}, 183 | "outputs": [ 184 | { 185 | "data": { 186 | "text/plain": [ 187 | "11" 188 | ] 189 | }, 190 | "execution_count": 15, 191 | "metadata": {}, 192 | "output_type": "execute_result" 193 | } 194 | ], 195 | "source": [ 196 | "len(x)" 197 | ] 198 | }, 199 | { 200 | "cell_type": "markdown", 201 | "metadata": {}, 202 | "source": [ 203 | "## length" 204 | ] 205 | }, 206 | { 207 | "cell_type": "code", 208 | "execution_count": 16, 209 | "metadata": {}, 210 | "outputs": [ 211 | { 212 | "data": { 213 | "text/plain": [ 214 | "11" 215 | ] 216 | }, 217 | "execution_count": 16, 218 | "metadata": {}, 219 | "output_type": "execute_result" 220 | } 221 | ], 222 | "source": [ 223 | "len(x)" 224 | ] 225 | }, 226 | { 227 | "cell_type": "code", 228 | "execution_count": 17, 229 | "metadata": {}, 230 | "outputs": [ 231 | { 232 | "name": "stdout", 233 | "output_type": "stream", 234 | "text": [ 235 | "hello world\n" 236 | ] 237 | } 238 | ], 239 | "source": [ 240 | "print(x)" 241 | ] 242 | }, 243 | { 244 | "cell_type": "markdown", 245 | "metadata": {}, 246 | "source": [ 247 | "## escape characters" 248 | ] 249 | }, 250 | { 251 | "cell_type": "code", 252 | "execution_count": 18, 253 | "metadata": {}, 254 | "outputs": [ 255 | { 256 | "name": "stdout", 257 | "output_type": "stream", 258 | "text": [ 259 | "hello python\n" 260 | ] 261 | } 262 | ], 263 | "source": [ 264 | "print(\"hello python\")" 265 | ] 266 | }, 267 | { 268 | "cell_type": "code", 269 | "execution_count": 22, 270 | "metadata": {}, 271 | "outputs": [ 272 | { 273 | "name": "stdout", 274 | "output_type": "stream", 275 | "text": [ 276 | "hello \n", 277 | "python\n" 278 | ] 279 | } 280 | ], 281 | "source": [ 282 | "print(\"hello \\npython\")" 283 | ] 284 | }, 285 | { 286 | "cell_type": "code", 287 | "execution_count": 23, 288 | "metadata": {}, 289 | "outputs": [ 290 | { 291 | "name": "stdout", 292 | "output_type": "stream", 293 | "text": [ 294 | "hello \tpython\n" 295 | ] 296 | } 297 | ], 298 | "source": [ 299 | "print(\"hello \\tpython\")" 300 | ] 301 | }, 302 | { 303 | "cell_type": "code", 304 | "execution_count": null, 305 | "metadata": {}, 306 | "outputs": [], 307 | "source": [] 308 | } 309 | ], 310 | "metadata": { 311 | "kernelspec": { 312 | "display_name": "Python 3", 313 | "language": "python", 314 | "name": "python3" 315 | }, 316 | "language_info": { 317 | "codemirror_mode": { 318 | "name": "ipython", 319 | "version": 3 320 | }, 321 | "file_extension": ".py", 322 | "mimetype": "text/x-python", 323 | "name": "python", 324 | "nbconvert_exporter": "python", 325 | "pygments_lexer": "ipython3", 326 | "version": "3.6.4" 327 | } 328 | }, 329 | "nbformat": 4, 330 | "nbformat_minor": 2 331 | } 332 | -------------------------------------------------------------------------------- /03-StringsAdvanced.ipynb: -------------------------------------------------------------------------------- 1 | { 2 | "cells": [ 3 | { 4 | "cell_type": "code", 5 | "execution_count": 1, 6 | "metadata": {}, 7 | "outputs": [], 8 | "source": [ 9 | "my_string = \"hello world\"" 10 | ] 11 | }, 12 | { 13 | "cell_type": "code", 14 | "execution_count": 2, 15 | "metadata": {}, 16 | "outputs": [ 17 | { 18 | "data": { 19 | "text/plain": [ 20 | "'hello world'" 21 | ] 22 | }, 23 | "execution_count": 2, 24 | "metadata": {}, 25 | "output_type": "execute_result" 26 | } 27 | ], 28 | "source": [ 29 | "my_string" 30 | ] 31 | }, 32 | { 33 | "cell_type": "markdown", 34 | "metadata": {}, 35 | "source": [ 36 | "## indexing" 37 | ] 38 | }, 39 | { 40 | "cell_type": "code", 41 | "execution_count": 3, 42 | "metadata": {}, 43 | "outputs": [ 44 | { 45 | "data": { 46 | "text/plain": [ 47 | "'h'" 48 | ] 49 | }, 50 | "execution_count": 3, 51 | "metadata": {}, 52 | "output_type": "execute_result" 53 | } 54 | ], 55 | "source": [ 56 | "my_string[0]" 57 | ] 58 | }, 59 | { 60 | "cell_type": "code", 61 | "execution_count": 4, 62 | "metadata": {}, 63 | "outputs": [ 64 | { 65 | "data": { 66 | "text/plain": [ 67 | "'o'" 68 | ] 69 | }, 70 | "execution_count": 4, 71 | "metadata": {}, 72 | "output_type": "execute_result" 73 | } 74 | ], 75 | "source": [ 76 | "my_string[4]" 77 | ] 78 | }, 79 | { 80 | "cell_type": "code", 81 | "execution_count": 5, 82 | "metadata": {}, 83 | "outputs": [ 84 | { 85 | "data": { 86 | "text/plain": [ 87 | "'d'" 88 | ] 89 | }, 90 | "execution_count": 5, 91 | "metadata": {}, 92 | "output_type": "execute_result" 93 | } 94 | ], 95 | "source": [ 96 | "my_string[-1]" 97 | ] 98 | }, 99 | { 100 | "cell_type": "code", 101 | "execution_count": 6, 102 | "metadata": {}, 103 | "outputs": [ 104 | { 105 | "data": { 106 | "text/plain": [ 107 | "'l'" 108 | ] 109 | }, 110 | "execution_count": 6, 111 | "metadata": {}, 112 | "output_type": "execute_result" 113 | } 114 | ], 115 | "source": [ 116 | "my_string[-2]" 117 | ] 118 | }, 119 | { 120 | "cell_type": "code", 121 | "execution_count": 7, 122 | "metadata": {}, 123 | "outputs": [], 124 | "source": [ 125 | "my_string_2 = \"1234567890\"" 126 | ] 127 | }, 128 | { 129 | "cell_type": "code", 130 | "execution_count": 8, 131 | "metadata": {}, 132 | "outputs": [ 133 | { 134 | "data": { 135 | "text/plain": [ 136 | "'1'" 137 | ] 138 | }, 139 | "execution_count": 8, 140 | "metadata": {}, 141 | "output_type": "execute_result" 142 | } 143 | ], 144 | "source": [ 145 | "my_string_2[0]" 146 | ] 147 | }, 148 | { 149 | "cell_type": "code", 150 | "execution_count": 9, 151 | "metadata": {}, 152 | "outputs": [ 153 | { 154 | "data": { 155 | "text/plain": [ 156 | "'34567890'" 157 | ] 158 | }, 159 | "execution_count": 9, 160 | "metadata": {}, 161 | "output_type": "execute_result" 162 | } 163 | ], 164 | "source": [ 165 | "my_string_2[2:]" 166 | ] 167 | }, 168 | { 169 | "cell_type": "markdown", 170 | "metadata": {}, 171 | "source": [ 172 | "## slicing" 173 | ] 174 | }, 175 | { 176 | "cell_type": "code", 177 | "execution_count": 11, 178 | "metadata": {}, 179 | "outputs": [ 180 | { 181 | "data": { 182 | "text/plain": [ 183 | "'567890'" 184 | ] 185 | }, 186 | "execution_count": 11, 187 | "metadata": {}, 188 | "output_type": "execute_result" 189 | } 190 | ], 191 | "source": [ 192 | "my_string_2[4:]" 193 | ] 194 | }, 195 | { 196 | "cell_type": "code", 197 | "execution_count": 12, 198 | "metadata": {}, 199 | "outputs": [ 200 | { 201 | "data": { 202 | "text/plain": [ 203 | "'12'" 204 | ] 205 | }, 206 | "execution_count": 12, 207 | "metadata": {}, 208 | "output_type": "execute_result" 209 | } 210 | ], 211 | "source": [ 212 | "my_string_2[:2]" 213 | ] 214 | }, 215 | { 216 | "cell_type": "markdown", 217 | "metadata": {}, 218 | "source": [ 219 | "## stopping index" 220 | ] 221 | }, 222 | { 223 | "cell_type": "code", 224 | "execution_count": 13, 225 | "metadata": {}, 226 | "outputs": [ 227 | { 228 | "data": { 229 | "text/plain": [ 230 | "'1234'" 231 | ] 232 | }, 233 | "execution_count": 13, 234 | "metadata": {}, 235 | "output_type": "execute_result" 236 | } 237 | ], 238 | "source": [ 239 | "my_string_2[:4]" 240 | ] 241 | }, 242 | { 243 | "cell_type": "code", 244 | "execution_count": 14, 245 | "metadata": {}, 246 | "outputs": [ 247 | { 248 | "data": { 249 | "text/plain": [ 250 | "'34'" 251 | ] 252 | }, 253 | "execution_count": 14, 254 | "metadata": {}, 255 | "output_type": "execute_result" 256 | } 257 | ], 258 | "source": [ 259 | "my_string_2[2:4]" 260 | ] 261 | }, 262 | { 263 | "cell_type": "code", 264 | "execution_count": 15, 265 | "metadata": {}, 266 | "outputs": [ 267 | { 268 | "data": { 269 | "text/plain": [ 270 | "'678'" 271 | ] 272 | }, 273 | "execution_count": 15, 274 | "metadata": {}, 275 | "output_type": "execute_result" 276 | } 277 | ], 278 | "source": [ 279 | "my_string_2[5:8]" 280 | ] 281 | }, 282 | { 283 | "cell_type": "markdown", 284 | "metadata": {}, 285 | "source": [ 286 | "## step size" 287 | ] 288 | }, 289 | { 290 | "cell_type": "code", 291 | "execution_count": 16, 292 | "metadata": {}, 293 | "outputs": [ 294 | { 295 | "data": { 296 | "text/plain": [ 297 | "'1234567890'" 298 | ] 299 | }, 300 | "execution_count": 16, 301 | "metadata": {}, 302 | "output_type": "execute_result" 303 | } 304 | ], 305 | "source": [ 306 | "my_string_2[::]" 307 | ] 308 | }, 309 | { 310 | "cell_type": "code", 311 | "execution_count": 17, 312 | "metadata": {}, 313 | "outputs": [ 314 | { 315 | "data": { 316 | "text/plain": [ 317 | "'1470'" 318 | ] 319 | }, 320 | "execution_count": 17, 321 | "metadata": {}, 322 | "output_type": "execute_result" 323 | } 324 | ], 325 | "source": [ 326 | "my_string_2[::3]" 327 | ] 328 | }, 329 | { 330 | "cell_type": "code", 331 | "execution_count": 18, 332 | "metadata": {}, 333 | "outputs": [ 334 | { 335 | "data": { 336 | "text/plain": [ 337 | "'13579'" 338 | ] 339 | }, 340 | "execution_count": 18, 341 | "metadata": {}, 342 | "output_type": "execute_result" 343 | } 344 | ], 345 | "source": [ 346 | "my_string_2[::2]" 347 | ] 348 | }, 349 | { 350 | "cell_type": "code", 351 | "execution_count": 19, 352 | "metadata": {}, 353 | "outputs": [ 354 | { 355 | "data": { 356 | "text/plain": [ 357 | "'3'" 358 | ] 359 | }, 360 | "execution_count": 19, 361 | "metadata": {}, 362 | "output_type": "execute_result" 363 | } 364 | ], 365 | "source": [ 366 | "my_string_2[2:4:2]" 367 | ] 368 | }, 369 | { 370 | "cell_type": "code", 371 | "execution_count": 20, 372 | "metadata": {}, 373 | "outputs": [ 374 | { 375 | "data": { 376 | "text/plain": [ 377 | "'0987654321'" 378 | ] 379 | }, 380 | "execution_count": 20, 381 | "metadata": {}, 382 | "output_type": "execute_result" 383 | } 384 | ], 385 | "source": [ 386 | "my_string_2[::-1]" 387 | ] 388 | }, 389 | { 390 | "cell_type": "markdown", 391 | "metadata": {}, 392 | "source": [ 393 | "## string methods" 394 | ] 395 | }, 396 | { 397 | "cell_type": "code", 398 | "execution_count": 23, 399 | "metadata": {}, 400 | "outputs": [], 401 | "source": [ 402 | "my_name = \"atil\"" 403 | ] 404 | }, 405 | { 406 | "cell_type": "code", 407 | "execution_count": 27, 408 | "metadata": {}, 409 | "outputs": [], 410 | "source": [ 411 | "my_name_capitalized = my_name.capitalize()" 412 | ] 413 | }, 414 | { 415 | "cell_type": "code", 416 | "execution_count": 28, 417 | "metadata": {}, 418 | "outputs": [ 419 | { 420 | "data": { 421 | "text/plain": [ 422 | "'atil'" 423 | ] 424 | }, 425 | "execution_count": 28, 426 | "metadata": {}, 427 | "output_type": "execute_result" 428 | } 429 | ], 430 | "source": [ 431 | "my_name" 432 | ] 433 | }, 434 | { 435 | "cell_type": "code", 436 | "execution_count": 29, 437 | "metadata": {}, 438 | "outputs": [ 439 | { 440 | "data": { 441 | "text/plain": [ 442 | "'Atil'" 443 | ] 444 | }, 445 | "execution_count": 29, 446 | "metadata": {}, 447 | "output_type": "execute_result" 448 | } 449 | ], 450 | "source": [ 451 | "my_name_capitalized" 452 | ] 453 | }, 454 | { 455 | "cell_type": "code", 456 | "execution_count": 30, 457 | "metadata": {}, 458 | "outputs": [], 459 | "source": [ 460 | "my_name = \"Atil Samancioglu\"" 461 | ] 462 | }, 463 | { 464 | "cell_type": "code", 465 | "execution_count": 31, 466 | "metadata": {}, 467 | "outputs": [ 468 | { 469 | "data": { 470 | "text/plain": [ 471 | "['Atil', 'Samancioglu']" 472 | ] 473 | }, 474 | "execution_count": 31, 475 | "metadata": {}, 476 | "output_type": "execute_result" 477 | } 478 | ], 479 | "source": [ 480 | "my_name.split()" 481 | ] 482 | }, 483 | { 484 | "cell_type": "code", 485 | "execution_count": 32, 486 | "metadata": {}, 487 | "outputs": [ 488 | { 489 | "data": { 490 | "text/plain": [ 491 | "'Atil Samancioglu'" 492 | ] 493 | }, 494 | "execution_count": 32, 495 | "metadata": {}, 496 | "output_type": "execute_result" 497 | } 498 | ], 499 | "source": [ 500 | "my_name" 501 | ] 502 | }, 503 | { 504 | "cell_type": "code", 505 | "execution_count": 33, 506 | "metadata": {}, 507 | "outputs": [], 508 | "source": [ 509 | "my_name_split = my_name.split()" 510 | ] 511 | }, 512 | { 513 | "cell_type": "code", 514 | "execution_count": 37, 515 | "metadata": {}, 516 | "outputs": [ 517 | { 518 | "data": { 519 | "text/plain": [ 520 | "['Atil', 'Samancioglu']" 521 | ] 522 | }, 523 | "execution_count": 37, 524 | "metadata": {}, 525 | "output_type": "execute_result" 526 | } 527 | ], 528 | "source": [ 529 | "my_name_split" 530 | ] 531 | }, 532 | { 533 | "cell_type": "code", 534 | "execution_count": 38, 535 | "metadata": {}, 536 | "outputs": [], 537 | "source": [ 538 | "my_number = 123" 539 | ] 540 | }, 541 | { 542 | "cell_type": "code", 543 | "execution_count": 39, 544 | "metadata": {}, 545 | "outputs": [ 546 | { 547 | "data": { 548 | "text/plain": [ 549 | "'ATIL SAMANCIOGLU'" 550 | ] 551 | }, 552 | "execution_count": 39, 553 | "metadata": {}, 554 | "output_type": "execute_result" 555 | } 556 | ], 557 | "source": [ 558 | "my_name.upper()" 559 | ] 560 | }, 561 | { 562 | "cell_type": "code", 563 | "execution_count": 43, 564 | "metadata": {}, 565 | "outputs": [ 566 | { 567 | "data": { 568 | "text/plain": [ 569 | "'jamesjamesjamesjamesjamesjamesjamesjamesjamesjames'" 570 | ] 571 | }, 572 | "execution_count": 43, 573 | "metadata": {}, 574 | "output_type": "execute_result" 575 | } 576 | ], 577 | "source": [ 578 | "\"james\" * 10" 579 | ] 580 | }, 581 | { 582 | "cell_type": "code", 583 | "execution_count": 46, 584 | "metadata": {}, 585 | "outputs": [ 586 | { 587 | "data": { 588 | "text/plain": [ 589 | "'jameslars'" 590 | ] 591 | }, 592 | "execution_count": 46, 593 | "metadata": {}, 594 | "output_type": "execute_result" 595 | } 596 | ], 597 | "source": [ 598 | "\"james\" + \"lars\"" 599 | ] 600 | }, 601 | { 602 | "cell_type": "code", 603 | "execution_count": 47, 604 | "metadata": {}, 605 | "outputs": [], 606 | "source": [ 607 | "my_name = \"Atil\"" 608 | ] 609 | }, 610 | { 611 | "cell_type": "code", 612 | "execution_count": 54, 613 | "metadata": {}, 614 | "outputs": [], 615 | "source": [ 616 | "my_surname = \"Samancioglu\"" 617 | ] 618 | }, 619 | { 620 | "cell_type": "code", 621 | "execution_count": 55, 622 | "metadata": {}, 623 | "outputs": [], 624 | "source": [ 625 | "my_full_name = my_name + \" \" + my_surname" 626 | ] 627 | }, 628 | { 629 | "cell_type": "code", 630 | "execution_count": 56, 631 | "metadata": {}, 632 | "outputs": [ 633 | { 634 | "data": { 635 | "text/plain": [ 636 | "'Atil Samancioglu'" 637 | ] 638 | }, 639 | "execution_count": 56, 640 | "metadata": {}, 641 | "output_type": "execute_result" 642 | } 643 | ], 644 | "source": [ 645 | "my_full_name" 646 | ] 647 | }, 648 | { 649 | "cell_type": "code", 650 | "execution_count": 58, 651 | "metadata": {}, 652 | "outputs": [ 653 | { 654 | "data": { 655 | "text/plain": [ 656 | "'jamesjamesjames'" 657 | ] 658 | }, 659 | "execution_count": 58, 660 | "metadata": {}, 661 | "output_type": "execute_result" 662 | } 663 | ], 664 | "source": [ 665 | "\"james\" * 3" 666 | ] 667 | }, 668 | { 669 | "cell_type": "code", 670 | "execution_count": null, 671 | "metadata": {}, 672 | "outputs": [], 673 | "source": [] 674 | } 675 | ], 676 | "metadata": { 677 | "kernelspec": { 678 | "display_name": "Python 3", 679 | "language": "python", 680 | "name": "python3" 681 | }, 682 | "language_info": { 683 | "codemirror_mode": { 684 | "name": "ipython", 685 | "version": 3 686 | }, 687 | "file_extension": ".py", 688 | "mimetype": "text/x-python", 689 | "name": "python", 690 | "nbconvert_exporter": "python", 691 | "pygments_lexer": "ipython3", 692 | "version": "3.6.4" 693 | } 694 | }, 695 | "nbformat": 4, 696 | "nbformat_minor": 2 697 | } 698 | -------------------------------------------------------------------------------- /04-Lists.ipynb: -------------------------------------------------------------------------------- 1 | { 2 | "cells": [ 3 | { 4 | "cell_type": "code", 5 | "execution_count": 1, 6 | "metadata": {}, 7 | "outputs": [], 8 | "source": [ 9 | "my_string = \"Atil\"" 10 | ] 11 | }, 12 | { 13 | "cell_type": "code", 14 | "execution_count": 2, 15 | "metadata": {}, 16 | "outputs": [ 17 | { 18 | "data": { 19 | "text/plain": [ 20 | "'A'" 21 | ] 22 | }, 23 | "execution_count": 2, 24 | "metadata": {}, 25 | "output_type": "execute_result" 26 | } 27 | ], 28 | "source": [ 29 | "my_string[0]" 30 | ] 31 | }, 32 | { 33 | "cell_type": "code", 34 | "execution_count": 3, 35 | "metadata": {}, 36 | "outputs": [ 37 | { 38 | "data": { 39 | "text/plain": [ 40 | "'t'" 41 | ] 42 | }, 43 | "execution_count": 3, 44 | "metadata": {}, 45 | "output_type": "execute_result" 46 | } 47 | ], 48 | "source": [ 49 | "my_string[1]" 50 | ] 51 | }, 52 | { 53 | "cell_type": "code", 54 | "execution_count": 6, 55 | "metadata": {}, 56 | "outputs": [], 57 | "source": [ 58 | "#my_string[0] = \"B\"" 59 | ] 60 | }, 61 | { 62 | "cell_type": "markdown", 63 | "metadata": {}, 64 | "source": [ 65 | "## immutability" 66 | ] 67 | }, 68 | { 69 | "cell_type": "code", 70 | "execution_count": 7, 71 | "metadata": {}, 72 | "outputs": [], 73 | "source": [ 74 | "#my_string[2] = \"G\"" 75 | ] 76 | }, 77 | { 78 | "cell_type": "code", 79 | "execution_count": 8, 80 | "metadata": {}, 81 | "outputs": [], 82 | "source": [ 83 | "my_list = [1,2,3]" 84 | ] 85 | }, 86 | { 87 | "cell_type": "code", 88 | "execution_count": 9, 89 | "metadata": {}, 90 | "outputs": [ 91 | { 92 | "data": { 93 | "text/plain": [ 94 | "1" 95 | ] 96 | }, 97 | "execution_count": 9, 98 | "metadata": {}, 99 | "output_type": "execute_result" 100 | } 101 | ], 102 | "source": [ 103 | "my_list[0]" 104 | ] 105 | }, 106 | { 107 | "cell_type": "code", 108 | "execution_count": 10, 109 | "metadata": {}, 110 | "outputs": [], 111 | "source": [ 112 | "my_list[0] = 5" 113 | ] 114 | }, 115 | { 116 | "cell_type": "code", 117 | "execution_count": 11, 118 | "metadata": {}, 119 | "outputs": [ 120 | { 121 | "data": { 122 | "text/plain": [ 123 | "[5, 2, 3]" 124 | ] 125 | }, 126 | "execution_count": 11, 127 | "metadata": {}, 128 | "output_type": "execute_result" 129 | } 130 | ], 131 | "source": [ 132 | "my_list" 133 | ] 134 | }, 135 | { 136 | "cell_type": "markdown", 137 | "metadata": {}, 138 | "source": [ 139 | "## mutable" 140 | ] 141 | }, 142 | { 143 | "cell_type": "code", 144 | "execution_count": 12, 145 | "metadata": {}, 146 | "outputs": [], 147 | "source": [ 148 | "my_list[2] = 6" 149 | ] 150 | }, 151 | { 152 | "cell_type": "code", 153 | "execution_count": 13, 154 | "metadata": {}, 155 | "outputs": [ 156 | { 157 | "data": { 158 | "text/plain": [ 159 | "[5, 2, 6]" 160 | ] 161 | }, 162 | "execution_count": 13, 163 | "metadata": {}, 164 | "output_type": "execute_result" 165 | } 166 | ], 167 | "source": [ 168 | "my_list" 169 | ] 170 | }, 171 | { 172 | "cell_type": "code", 173 | "execution_count": 14, 174 | "metadata": {}, 175 | "outputs": [], 176 | "source": [ 177 | "my_list.append(7)" 178 | ] 179 | }, 180 | { 181 | "cell_type": "code", 182 | "execution_count": 15, 183 | "metadata": {}, 184 | "outputs": [ 185 | { 186 | "data": { 187 | "text/plain": [ 188 | "[5, 2, 6, 7]" 189 | ] 190 | }, 191 | "execution_count": 15, 192 | "metadata": {}, 193 | "output_type": "execute_result" 194 | } 195 | ], 196 | "source": [ 197 | "my_list" 198 | ] 199 | }, 200 | { 201 | "cell_type": "code", 202 | "execution_count": 16, 203 | "metadata": {}, 204 | "outputs": [], 205 | "source": [ 206 | "my_string = \"lars\"" 207 | ] 208 | }, 209 | { 210 | "cell_type": "code", 211 | "execution_count": 17, 212 | "metadata": {}, 213 | "outputs": [ 214 | { 215 | "data": { 216 | "text/plain": [ 217 | "'Lars'" 218 | ] 219 | }, 220 | "execution_count": 17, 221 | "metadata": {}, 222 | "output_type": "execute_result" 223 | } 224 | ], 225 | "source": [ 226 | "my_string.capitalize()" 227 | ] 228 | }, 229 | { 230 | "cell_type": "code", 231 | "execution_count": 18, 232 | "metadata": {}, 233 | "outputs": [ 234 | { 235 | "data": { 236 | "text/plain": [ 237 | "'lars'" 238 | ] 239 | }, 240 | "execution_count": 18, 241 | "metadata": {}, 242 | "output_type": "execute_result" 243 | } 244 | ], 245 | "source": [ 246 | "my_string" 247 | ] 248 | }, 249 | { 250 | "cell_type": "code", 251 | "execution_count": 19, 252 | "metadata": {}, 253 | "outputs": [ 254 | { 255 | "data": { 256 | "text/plain": [ 257 | "[5, 2, 6, 7]" 258 | ] 259 | }, 260 | "execution_count": 19, 261 | "metadata": {}, 262 | "output_type": "execute_result" 263 | } 264 | ], 265 | "source": [ 266 | "my_list" 267 | ] 268 | }, 269 | { 270 | "cell_type": "code", 271 | "execution_count": 20, 272 | "metadata": {}, 273 | "outputs": [ 274 | { 275 | "data": { 276 | "text/plain": [ 277 | "7" 278 | ] 279 | }, 280 | "execution_count": 20, 281 | "metadata": {}, 282 | "output_type": "execute_result" 283 | } 284 | ], 285 | "source": [ 286 | "my_list.pop()" 287 | ] 288 | }, 289 | { 290 | "cell_type": "code", 291 | "execution_count": 21, 292 | "metadata": {}, 293 | "outputs": [ 294 | { 295 | "data": { 296 | "text/plain": [ 297 | "[5, 2, 6]" 298 | ] 299 | }, 300 | "execution_count": 21, 301 | "metadata": {}, 302 | "output_type": "execute_result" 303 | } 304 | ], 305 | "source": [ 306 | "my_list" 307 | ] 308 | }, 309 | { 310 | "cell_type": "code", 311 | "execution_count": 22, 312 | "metadata": {}, 313 | "outputs": [], 314 | "source": [ 315 | "my_mixed_list = [1,2,\"a\",\"bhf\"]" 316 | ] 317 | }, 318 | { 319 | "cell_type": "code", 320 | "execution_count": 23, 321 | "metadata": {}, 322 | "outputs": [ 323 | { 324 | "data": { 325 | "text/plain": [ 326 | "1" 327 | ] 328 | }, 329 | "execution_count": 23, 330 | "metadata": {}, 331 | "output_type": "execute_result" 332 | } 333 | ], 334 | "source": [ 335 | "my_mixed_list[0]" 336 | ] 337 | }, 338 | { 339 | "cell_type": "code", 340 | "execution_count": 24, 341 | "metadata": {}, 342 | "outputs": [ 343 | { 344 | "data": { 345 | "text/plain": [ 346 | "'bhf'" 347 | ] 348 | }, 349 | "execution_count": 24, 350 | "metadata": {}, 351 | "output_type": "execute_result" 352 | } 353 | ], 354 | "source": [ 355 | "my_mixed_list[-1]" 356 | ] 357 | }, 358 | { 359 | "cell_type": "code", 360 | "execution_count": 35, 361 | "metadata": {}, 362 | "outputs": [], 363 | "source": [ 364 | "my_list_1 = [\"a\",\"b\",\"c\"]" 365 | ] 366 | }, 367 | { 368 | "cell_type": "code", 369 | "execution_count": 36, 370 | "metadata": {}, 371 | "outputs": [], 372 | "source": [ 373 | "my_list_2 = [\"d\",\"e\",\"f\"]" 374 | ] 375 | }, 376 | { 377 | "cell_type": "code", 378 | "execution_count": 37, 379 | "metadata": {}, 380 | "outputs": [], 381 | "source": [ 382 | "my_list_3 = my_list_1 + my_list_2" 383 | ] 384 | }, 385 | { 386 | "cell_type": "code", 387 | "execution_count": 38, 388 | "metadata": {}, 389 | "outputs": [ 390 | { 391 | "data": { 392 | "text/plain": [ 393 | "['a', 'b', 'c', 'd', 'e', 'f']" 394 | ] 395 | }, 396 | "execution_count": 38, 397 | "metadata": {}, 398 | "output_type": "execute_result" 399 | } 400 | ], 401 | "source": [ 402 | "my_list_3" 403 | ] 404 | }, 405 | { 406 | "cell_type": "code", 407 | "execution_count": 39, 408 | "metadata": {}, 409 | "outputs": [ 410 | { 411 | "data": { 412 | "text/plain": [ 413 | "['a', 'b', 'c', 'a', 'b', 'c', 'a', 'b', 'c']" 414 | ] 415 | }, 416 | "execution_count": 39, 417 | "metadata": {}, 418 | "output_type": "execute_result" 419 | } 420 | ], 421 | "source": [ 422 | "my_list_1 * 3" 423 | ] 424 | }, 425 | { 426 | "cell_type": "code", 427 | "execution_count": 42, 428 | "metadata": {}, 429 | "outputs": [], 430 | "source": [ 431 | "my_list_1.reverse()" 432 | ] 433 | }, 434 | { 435 | "cell_type": "code", 436 | "execution_count": 43, 437 | "metadata": {}, 438 | "outputs": [ 439 | { 440 | "data": { 441 | "text/plain": [ 442 | "['c', 'b', 'a']" 443 | ] 444 | }, 445 | "execution_count": 43, 446 | "metadata": {}, 447 | "output_type": "execute_result" 448 | } 449 | ], 450 | "source": [ 451 | "my_list_1" 452 | ] 453 | }, 454 | { 455 | "cell_type": "markdown", 456 | "metadata": {}, 457 | "source": [ 458 | "## nested list" 459 | ] 460 | }, 461 | { 462 | "cell_type": "code", 463 | "execution_count": 1, 464 | "metadata": {}, 465 | "outputs": [], 466 | "source": [ 467 | "new_list = [1,4,\"a\"]" 468 | ] 469 | }, 470 | { 471 | "cell_type": "code", 472 | "execution_count": 2, 473 | "metadata": {}, 474 | "outputs": [], 475 | "source": [ 476 | "new_list = [1,4,\"a\",[3,\"c\"]]" 477 | ] 478 | }, 479 | { 480 | "cell_type": "code", 481 | "execution_count": 7, 482 | "metadata": {}, 483 | "outputs": [ 484 | { 485 | "data": { 486 | "text/plain": [ 487 | "'a'" 488 | ] 489 | }, 490 | "execution_count": 7, 491 | "metadata": {}, 492 | "output_type": "execute_result" 493 | } 494 | ], 495 | "source": [ 496 | "new_list[2]" 497 | ] 498 | }, 499 | { 500 | "cell_type": "code", 501 | "execution_count": 8, 502 | "metadata": {}, 503 | "outputs": [ 504 | { 505 | "data": { 506 | "text/plain": [ 507 | "[3, 'c']" 508 | ] 509 | }, 510 | "execution_count": 8, 511 | "metadata": {}, 512 | "output_type": "execute_result" 513 | } 514 | ], 515 | "source": [ 516 | "new_list[3]" 517 | ] 518 | }, 519 | { 520 | "cell_type": "code", 521 | "execution_count": 9, 522 | "metadata": {}, 523 | "outputs": [], 524 | "source": [ 525 | "nested_list = new_list[3]" 526 | ] 527 | }, 528 | { 529 | "cell_type": "code", 530 | "execution_count": 10, 531 | "metadata": {}, 532 | "outputs": [ 533 | { 534 | "data": { 535 | "text/plain": [ 536 | "[3, 'c']" 537 | ] 538 | }, 539 | "execution_count": 10, 540 | "metadata": {}, 541 | "output_type": "execute_result" 542 | } 543 | ], 544 | "source": [ 545 | "nested_list" 546 | ] 547 | }, 548 | { 549 | "cell_type": "code", 550 | "execution_count": 11, 551 | "metadata": {}, 552 | "outputs": [ 553 | { 554 | "data": { 555 | "text/plain": [ 556 | "'c'" 557 | ] 558 | }, 559 | "execution_count": 11, 560 | "metadata": {}, 561 | "output_type": "execute_result" 562 | } 563 | ], 564 | "source": [ 565 | "nested_list[1]" 566 | ] 567 | }, 568 | { 569 | "cell_type": "code", 570 | "execution_count": 12, 571 | "metadata": {}, 572 | "outputs": [ 573 | { 574 | "data": { 575 | "text/plain": [ 576 | "'c'" 577 | ] 578 | }, 579 | "execution_count": 12, 580 | "metadata": {}, 581 | "output_type": "execute_result" 582 | } 583 | ], 584 | "source": [ 585 | "new_list[3][1]" 586 | ] 587 | }, 588 | { 589 | "cell_type": "code", 590 | "execution_count": 13, 591 | "metadata": {}, 592 | "outputs": [ 593 | { 594 | "data": { 595 | "text/plain": [ 596 | "[1, 4, 'a', [3, 'c']]" 597 | ] 598 | }, 599 | "execution_count": 13, 600 | "metadata": {}, 601 | "output_type": "execute_result" 602 | } 603 | ], 604 | "source": [ 605 | "new_list" 606 | ] 607 | }, 608 | { 609 | "cell_type": "code", 610 | "execution_count": 14, 611 | "metadata": {}, 612 | "outputs": [ 613 | { 614 | "data": { 615 | "text/plain": [ 616 | "['a', [3, 'c']]" 617 | ] 618 | }, 619 | "execution_count": 14, 620 | "metadata": {}, 621 | "output_type": "execute_result" 622 | } 623 | ], 624 | "source": [ 625 | "new_list[2:]" 626 | ] 627 | }, 628 | { 629 | "cell_type": "code", 630 | "execution_count": 15, 631 | "metadata": {}, 632 | "outputs": [ 633 | { 634 | "data": { 635 | "text/plain": [ 636 | "[1, 4]" 637 | ] 638 | }, 639 | "execution_count": 15, 640 | "metadata": {}, 641 | "output_type": "execute_result" 642 | } 643 | ], 644 | "source": [ 645 | "new_list[:2]" 646 | ] 647 | }, 648 | { 649 | "cell_type": "code", 650 | "execution_count": null, 651 | "metadata": {}, 652 | "outputs": [], 653 | "source": [] 654 | } 655 | ], 656 | "metadata": { 657 | "kernelspec": { 658 | "display_name": "Python 3", 659 | "language": "python", 660 | "name": "python3" 661 | }, 662 | "language_info": { 663 | "codemirror_mode": { 664 | "name": "ipython", 665 | "version": 3 666 | }, 667 | "file_extension": ".py", 668 | "mimetype": "text/x-python", 669 | "name": "python", 670 | "nbconvert_exporter": "python", 671 | "pygments_lexer": "ipython3", 672 | "version": "3.6.4" 673 | } 674 | }, 675 | "nbformat": 4, 676 | "nbformat_minor": 2 677 | } 678 | -------------------------------------------------------------------------------- /05-Dictionary.ipynb: -------------------------------------------------------------------------------- 1 | { 2 | "cells": [ 3 | { 4 | "cell_type": "code", 5 | "execution_count": 1, 6 | "metadata": {}, 7 | "outputs": [], 8 | "source": [ 9 | "my_dictionary = {\"key\":\"value\"}" 10 | ] 11 | }, 12 | { 13 | "cell_type": "code", 14 | "execution_count": 2, 15 | "metadata": {}, 16 | "outputs": [ 17 | { 18 | "data": { 19 | "text/plain": [ 20 | "'value'" 21 | ] 22 | }, 23 | "execution_count": 2, 24 | "metadata": {}, 25 | "output_type": "execute_result" 26 | } 27 | ], 28 | "source": [ 29 | "my_dictionary[\"key\"]" 30 | ] 31 | }, 32 | { 33 | "cell_type": "code", 34 | "execution_count": 3, 35 | "metadata": {}, 36 | "outputs": [], 37 | "source": [ 38 | "my_list = [100,200]" 39 | ] 40 | }, 41 | { 42 | "cell_type": "code", 43 | "execution_count": 4, 44 | "metadata": {}, 45 | "outputs": [], 46 | "source": [ 47 | "my_list_2 = [\"run\",\"swim\"]" 48 | ] 49 | }, 50 | { 51 | "cell_type": "code", 52 | "execution_count": 5, 53 | "metadata": {}, 54 | "outputs": [ 55 | { 56 | "data": { 57 | "text/plain": [ 58 | "100" 59 | ] 60 | }, 61 | "execution_count": 5, 62 | "metadata": {}, 63 | "output_type": "execute_result" 64 | } 65 | ], 66 | "source": [ 67 | "my_list[0]" 68 | ] 69 | }, 70 | { 71 | "cell_type": "code", 72 | "execution_count": 6, 73 | "metadata": {}, 74 | "outputs": [ 75 | { 76 | "data": { 77 | "text/plain": [ 78 | "'run'" 79 | ] 80 | }, 81 | "execution_count": 6, 82 | "metadata": {}, 83 | "output_type": "execute_result" 84 | } 85 | ], 86 | "source": [ 87 | "my_list_2[0]" 88 | ] 89 | }, 90 | { 91 | "cell_type": "code", 92 | "execution_count": 7, 93 | "metadata": {}, 94 | "outputs": [], 95 | "source": [ 96 | "my_fitness_dictionary = {\"run\":100,\"swim\":200}" 97 | ] 98 | }, 99 | { 100 | "cell_type": "code", 101 | "execution_count": 8, 102 | "metadata": {}, 103 | "outputs": [ 104 | { 105 | "data": { 106 | "text/plain": [ 107 | "100" 108 | ] 109 | }, 110 | "execution_count": 8, 111 | "metadata": {}, 112 | "output_type": "execute_result" 113 | } 114 | ], 115 | "source": [ 116 | "my_fitness_dictionary[\"run\"]" 117 | ] 118 | }, 119 | { 120 | "cell_type": "code", 121 | "execution_count": 9, 122 | "metadata": {}, 123 | "outputs": [ 124 | { 125 | "data": { 126 | "text/plain": [ 127 | "200" 128 | ] 129 | }, 130 | "execution_count": 9, 131 | "metadata": {}, 132 | "output_type": "execute_result" 133 | } 134 | ], 135 | "source": [ 136 | "my_fitness_dictionary[\"swim\"]" 137 | ] 138 | }, 139 | { 140 | "cell_type": "code", 141 | "execution_count": 10, 142 | "metadata": {}, 143 | "outputs": [], 144 | "source": [ 145 | "my_dictionary_2 = {\"key1\":1, \"key2\":2,\"key3\":\"apple\"}" 146 | ] 147 | }, 148 | { 149 | "cell_type": "code", 150 | "execution_count": 11, 151 | "metadata": {}, 152 | "outputs": [ 153 | { 154 | "data": { 155 | "text/plain": [ 156 | "1" 157 | ] 158 | }, 159 | "execution_count": 11, 160 | "metadata": {}, 161 | "output_type": "execute_result" 162 | } 163 | ], 164 | "source": [ 165 | "my_dictionary_2[\"key1\"]" 166 | ] 167 | }, 168 | { 169 | "cell_type": "code", 170 | "execution_count": 12, 171 | "metadata": {}, 172 | "outputs": [ 173 | { 174 | "data": { 175 | "text/plain": [ 176 | "'apple'" 177 | ] 178 | }, 179 | "execution_count": 12, 180 | "metadata": {}, 181 | "output_type": "execute_result" 182 | } 183 | ], 184 | "source": [ 185 | "my_dictionary_2[\"key3\"]" 186 | ] 187 | }, 188 | { 189 | "cell_type": "code", 190 | "execution_count": 13, 191 | "metadata": {}, 192 | "outputs": [], 193 | "source": [ 194 | "my_dictionary_3 = {\"key1\":10,20:30}" 195 | ] 196 | }, 197 | { 198 | "cell_type": "code", 199 | "execution_count": 14, 200 | "metadata": {}, 201 | "outputs": [ 202 | { 203 | "data": { 204 | "text/plain": [ 205 | "10" 206 | ] 207 | }, 208 | "execution_count": 14, 209 | "metadata": {}, 210 | "output_type": "execute_result" 211 | } 212 | ], 213 | "source": [ 214 | "my_dictionary_3[\"key1\"]" 215 | ] 216 | }, 217 | { 218 | "cell_type": "code", 219 | "execution_count": 15, 220 | "metadata": {}, 221 | "outputs": [ 222 | { 223 | "data": { 224 | "text/plain": [ 225 | "30" 226 | ] 227 | }, 228 | "execution_count": 15, 229 | "metadata": {}, 230 | "output_type": "execute_result" 231 | } 232 | ], 233 | "source": [ 234 | "my_dictionary_3[20]" 235 | ] 236 | }, 237 | { 238 | "cell_type": "code", 239 | "execution_count": 16, 240 | "metadata": {}, 241 | "outputs": [], 242 | "source": [ 243 | "my_dictionary_4 = {\"key1\" : 100, \"key2\" : [10,20,30], \"key3\" : {\"a\":5}}" 244 | ] 245 | }, 246 | { 247 | "cell_type": "code", 248 | "execution_count": 17, 249 | "metadata": {}, 250 | "outputs": [ 251 | { 252 | "data": { 253 | "text/plain": [ 254 | "{'key1': 100, 'key2': [10, 20, 30], 'key3': {'a': 5}}" 255 | ] 256 | }, 257 | "execution_count": 17, 258 | "metadata": {}, 259 | "output_type": "execute_result" 260 | } 261 | ], 262 | "source": [ 263 | "my_dictionary_4" 264 | ] 265 | }, 266 | { 267 | "cell_type": "code", 268 | "execution_count": 22, 269 | "metadata": {}, 270 | "outputs": [ 271 | { 272 | "data": { 273 | "text/plain": [ 274 | "dict_keys(['key1', 'key2', 'key3'])" 275 | ] 276 | }, 277 | "execution_count": 22, 278 | "metadata": {}, 279 | "output_type": "execute_result" 280 | } 281 | ], 282 | "source": [ 283 | "my_dictionary_4.keys()" 284 | ] 285 | }, 286 | { 287 | "cell_type": "code", 288 | "execution_count": 23, 289 | "metadata": {}, 290 | "outputs": [ 291 | { 292 | "data": { 293 | "text/plain": [ 294 | "dict_values([100, [10, 20, 30], {'a': 5}])" 295 | ] 296 | }, 297 | "execution_count": 23, 298 | "metadata": {}, 299 | "output_type": "execute_result" 300 | } 301 | ], 302 | "source": [ 303 | "my_dictionary_4.values()" 304 | ] 305 | }, 306 | { 307 | "cell_type": "code", 308 | "execution_count": 25, 309 | "metadata": {}, 310 | "outputs": [ 311 | { 312 | "data": { 313 | "text/plain": [ 314 | "5" 315 | ] 316 | }, 317 | "execution_count": 25, 318 | "metadata": {}, 319 | "output_type": "execute_result" 320 | } 321 | ], 322 | "source": [ 323 | "my_dictionary_4[\"key3\"][\"a\"]" 324 | ] 325 | }, 326 | { 327 | "cell_type": "code", 328 | "execution_count": 26, 329 | "metadata": {}, 330 | "outputs": [], 331 | "source": [ 332 | "my_dictionary_5 = {\"k1\":1,\"k2\":2}" 333 | ] 334 | }, 335 | { 336 | "cell_type": "code", 337 | "execution_count": 28, 338 | "metadata": {}, 339 | "outputs": [], 340 | "source": [ 341 | "my_dictionary_5[\"k1\"] = 3" 342 | ] 343 | }, 344 | { 345 | "cell_type": "code", 346 | "execution_count": 30, 347 | "metadata": {}, 348 | "outputs": [], 349 | "source": [ 350 | "my_dictionary_5[\"k3\"] = 7" 351 | ] 352 | }, 353 | { 354 | "cell_type": "code", 355 | "execution_count": 31, 356 | "metadata": {}, 357 | "outputs": [ 358 | { 359 | "data": { 360 | "text/plain": [ 361 | "{'k1': 3, 'k2': 2, 'k3': 7}" 362 | ] 363 | }, 364 | "execution_count": 31, 365 | "metadata": {}, 366 | "output_type": "execute_result" 367 | } 368 | ], 369 | "source": [ 370 | "my_dictionary_5" 371 | ] 372 | }, 373 | { 374 | "cell_type": "code", 375 | "execution_count": null, 376 | "metadata": {}, 377 | "outputs": [], 378 | "source": [] 379 | } 380 | ], 381 | "metadata": { 382 | "kernelspec": { 383 | "display_name": "Python 3", 384 | "language": "python", 385 | "name": "python3" 386 | }, 387 | "language_info": { 388 | "codemirror_mode": { 389 | "name": "ipython", 390 | "version": 3 391 | }, 392 | "file_extension": ".py", 393 | "mimetype": "text/x-python", 394 | "name": "python", 395 | "nbconvert_exporter": "python", 396 | "pygments_lexer": "ipython3", 397 | "version": "3.6.4" 398 | } 399 | }, 400 | "nbformat": 4, 401 | "nbformat_minor": 2 402 | } 403 | -------------------------------------------------------------------------------- /06-Set.ipynb: -------------------------------------------------------------------------------- 1 | { 2 | "cells": [ 3 | { 4 | "cell_type": "code", 5 | "execution_count": 2, 6 | "metadata": {}, 7 | "outputs": [], 8 | "source": [ 9 | "my_list = [1,2,3,1]" 10 | ] 11 | }, 12 | { 13 | "cell_type": "code", 14 | "execution_count": 3, 15 | "metadata": {}, 16 | "outputs": [ 17 | { 18 | "data": { 19 | "text/plain": [ 20 | "[1, 2, 3, 1]" 21 | ] 22 | }, 23 | "execution_count": 3, 24 | "metadata": {}, 25 | "output_type": "execute_result" 26 | } 27 | ], 28 | "source": [ 29 | "my_list" 30 | ] 31 | }, 32 | { 33 | "cell_type": "markdown", 34 | "metadata": {}, 35 | "source": [ 36 | "## casting" 37 | ] 38 | }, 39 | { 40 | "cell_type": "code", 41 | "execution_count": 4, 42 | "metadata": {}, 43 | "outputs": [], 44 | "source": [ 45 | "my_set = set(my_list)" 46 | ] 47 | }, 48 | { 49 | "cell_type": "code", 50 | "execution_count": 5, 51 | "metadata": {}, 52 | "outputs": [ 53 | { 54 | "data": { 55 | "text/plain": [ 56 | "{1, 2, 3}" 57 | ] 58 | }, 59 | "execution_count": 5, 60 | "metadata": {}, 61 | "output_type": "execute_result" 62 | } 63 | ], 64 | "source": [ 65 | "my_set" 66 | ] 67 | }, 68 | { 69 | "cell_type": "code", 70 | "execution_count": 6, 71 | "metadata": {}, 72 | "outputs": [], 73 | "source": [ 74 | "my_set_2 = {1,2,3,1}" 75 | ] 76 | }, 77 | { 78 | "cell_type": "code", 79 | "execution_count": 7, 80 | "metadata": {}, 81 | "outputs": [ 82 | { 83 | "data": { 84 | "text/plain": [ 85 | "{1, 2, 3}" 86 | ] 87 | }, 88 | "execution_count": 7, 89 | "metadata": {}, 90 | "output_type": "execute_result" 91 | } 92 | ], 93 | "source": [ 94 | "my_set_2" 95 | ] 96 | }, 97 | { 98 | "cell_type": "code", 99 | "execution_count": 8, 100 | "metadata": {}, 101 | "outputs": [ 102 | { 103 | "data": { 104 | "text/plain": [ 105 | "set" 106 | ] 107 | }, 108 | "execution_count": 8, 109 | "metadata": {}, 110 | "output_type": "execute_result" 111 | } 112 | ], 113 | "source": [ 114 | "type(my_set_2)" 115 | ] 116 | }, 117 | { 118 | "cell_type": "code", 119 | "execution_count": 9, 120 | "metadata": {}, 121 | "outputs": [], 122 | "source": [ 123 | "my_set_3 = {\"a\",\"b\",\"a\"}" 124 | ] 125 | }, 126 | { 127 | "cell_type": "code", 128 | "execution_count": 10, 129 | "metadata": {}, 130 | "outputs": [ 131 | { 132 | "data": { 133 | "text/plain": [ 134 | "{'a', 'b'}" 135 | ] 136 | }, 137 | "execution_count": 10, 138 | "metadata": {}, 139 | "output_type": "execute_result" 140 | } 141 | ], 142 | "source": [ 143 | "my_set_3" 144 | ] 145 | }, 146 | { 147 | "cell_type": "code", 148 | "execution_count": 11, 149 | "metadata": {}, 150 | "outputs": [], 151 | "source": [ 152 | "my_list = []" 153 | ] 154 | }, 155 | { 156 | "cell_type": "code", 157 | "execution_count": 12, 158 | "metadata": {}, 159 | "outputs": [ 160 | { 161 | "data": { 162 | "text/plain": [ 163 | "list" 164 | ] 165 | }, 166 | "execution_count": 12, 167 | "metadata": {}, 168 | "output_type": "execute_result" 169 | } 170 | ], 171 | "source": [ 172 | "type(my_list)" 173 | ] 174 | }, 175 | { 176 | "cell_type": "code", 177 | "execution_count": 13, 178 | "metadata": {}, 179 | "outputs": [ 180 | { 181 | "data": { 182 | "text/plain": [ 183 | "[]" 184 | ] 185 | }, 186 | "execution_count": 13, 187 | "metadata": {}, 188 | "output_type": "execute_result" 189 | } 190 | ], 191 | "source": [ 192 | "my_list" 193 | ] 194 | }, 195 | { 196 | "cell_type": "code", 197 | "execution_count": 14, 198 | "metadata": {}, 199 | "outputs": [], 200 | "source": [ 201 | "my_list.append(1)" 202 | ] 203 | }, 204 | { 205 | "cell_type": "code", 206 | "execution_count": 15, 207 | "metadata": {}, 208 | "outputs": [ 209 | { 210 | "data": { 211 | "text/plain": [ 212 | "[1]" 213 | ] 214 | }, 215 | "execution_count": 15, 216 | "metadata": {}, 217 | "output_type": "execute_result" 218 | } 219 | ], 220 | "source": [ 221 | "my_list" 222 | ] 223 | }, 224 | { 225 | "cell_type": "code", 226 | "execution_count": 16, 227 | "metadata": {}, 228 | "outputs": [], 229 | "source": [ 230 | "my_set_4 = {}" 231 | ] 232 | }, 233 | { 234 | "cell_type": "code", 235 | "execution_count": 17, 236 | "metadata": {}, 237 | "outputs": [ 238 | { 239 | "data": { 240 | "text/plain": [ 241 | "{}" 242 | ] 243 | }, 244 | "execution_count": 17, 245 | "metadata": {}, 246 | "output_type": "execute_result" 247 | } 248 | ], 249 | "source": [ 250 | "my_set_4" 251 | ] 252 | }, 253 | { 254 | "cell_type": "code", 255 | "execution_count": 18, 256 | "metadata": {}, 257 | "outputs": [ 258 | { 259 | "data": { 260 | "text/plain": [ 261 | "dict" 262 | ] 263 | }, 264 | "execution_count": 18, 265 | "metadata": {}, 266 | "output_type": "execute_result" 267 | } 268 | ], 269 | "source": [ 270 | "type(my_set_4)" 271 | ] 272 | }, 273 | { 274 | "cell_type": "code", 275 | "execution_count": 19, 276 | "metadata": {}, 277 | "outputs": [], 278 | "source": [ 279 | "my_set_4[\"key1\"] = 1" 280 | ] 281 | }, 282 | { 283 | "cell_type": "code", 284 | "execution_count": 20, 285 | "metadata": {}, 286 | "outputs": [ 287 | { 288 | "data": { 289 | "text/plain": [ 290 | "{'key1': 1}" 291 | ] 292 | }, 293 | "execution_count": 20, 294 | "metadata": {}, 295 | "output_type": "execute_result" 296 | } 297 | ], 298 | "source": [ 299 | "my_set_4" 300 | ] 301 | }, 302 | { 303 | "cell_type": "code", 304 | "execution_count": 21, 305 | "metadata": {}, 306 | "outputs": [], 307 | "source": [ 308 | "my_set_5 = set()" 309 | ] 310 | }, 311 | { 312 | "cell_type": "code", 313 | "execution_count": 22, 314 | "metadata": {}, 315 | "outputs": [ 316 | { 317 | "data": { 318 | "text/plain": [ 319 | "set()" 320 | ] 321 | }, 322 | "execution_count": 22, 323 | "metadata": {}, 324 | "output_type": "execute_result" 325 | } 326 | ], 327 | "source": [ 328 | "my_set_5" 329 | ] 330 | }, 331 | { 332 | "cell_type": "code", 333 | "execution_count": 23, 334 | "metadata": {}, 335 | "outputs": [], 336 | "source": [ 337 | "my_set_5.add(1)" 338 | ] 339 | }, 340 | { 341 | "cell_type": "code", 342 | "execution_count": 24, 343 | "metadata": {}, 344 | "outputs": [], 345 | "source": [ 346 | "my_set_5.add(2)" 347 | ] 348 | }, 349 | { 350 | "cell_type": "code", 351 | "execution_count": 25, 352 | "metadata": {}, 353 | "outputs": [ 354 | { 355 | "data": { 356 | "text/plain": [ 357 | "{1, 2}" 358 | ] 359 | }, 360 | "execution_count": 25, 361 | "metadata": {}, 362 | "output_type": "execute_result" 363 | } 364 | ], 365 | "source": [ 366 | "my_set_5" 367 | ] 368 | }, 369 | { 370 | "cell_type": "code", 371 | "execution_count": 26, 372 | "metadata": {}, 373 | "outputs": [], 374 | "source": [ 375 | "my_set_5.add(2)" 376 | ] 377 | }, 378 | { 379 | "cell_type": "code", 380 | "execution_count": 27, 381 | "metadata": {}, 382 | "outputs": [ 383 | { 384 | "data": { 385 | "text/plain": [ 386 | "{1, 2}" 387 | ] 388 | }, 389 | "execution_count": 27, 390 | "metadata": {}, 391 | "output_type": "execute_result" 392 | } 393 | ], 394 | "source": [ 395 | "my_set_5" 396 | ] 397 | }, 398 | { 399 | "cell_type": "code", 400 | "execution_count": 28, 401 | "metadata": {}, 402 | "outputs": [ 403 | { 404 | "data": { 405 | "text/plain": [ 406 | "set" 407 | ] 408 | }, 409 | "execution_count": 28, 410 | "metadata": {}, 411 | "output_type": "execute_result" 412 | } 413 | ], 414 | "source": [ 415 | "type(my_set_5)" 416 | ] 417 | }, 418 | { 419 | "cell_type": "code", 420 | "execution_count": 29, 421 | "metadata": {}, 422 | "outputs": [], 423 | "source": [ 424 | "my_dict_2 = dict()" 425 | ] 426 | }, 427 | { 428 | "cell_type": "code", 429 | "execution_count": 30, 430 | "metadata": {}, 431 | "outputs": [], 432 | "source": [ 433 | "my_dict_2[\"key1\"] = 1" 434 | ] 435 | }, 436 | { 437 | "cell_type": "code", 438 | "execution_count": 31, 439 | "metadata": {}, 440 | "outputs": [ 441 | { 442 | "data": { 443 | "text/plain": [ 444 | "{'key1': 1}" 445 | ] 446 | }, 447 | "execution_count": 31, 448 | "metadata": {}, 449 | "output_type": "execute_result" 450 | } 451 | ], 452 | "source": [ 453 | "my_dict_2" 454 | ] 455 | }, 456 | { 457 | "cell_type": "code", 458 | "execution_count": 32, 459 | "metadata": {}, 460 | "outputs": [], 461 | "source": [ 462 | "my_list_10 = list()" 463 | ] 464 | }, 465 | { 466 | "cell_type": "code", 467 | "execution_count": 33, 468 | "metadata": {}, 469 | "outputs": [ 470 | { 471 | "data": { 472 | "text/plain": [ 473 | "list" 474 | ] 475 | }, 476 | "execution_count": 33, 477 | "metadata": {}, 478 | "output_type": "execute_result" 479 | } 480 | ], 481 | "source": [ 482 | "type(my_list_10)" 483 | ] 484 | }, 485 | { 486 | "cell_type": "code", 487 | "execution_count": 34, 488 | "metadata": {}, 489 | "outputs": [ 490 | { 491 | "data": { 492 | "text/plain": [ 493 | "[]" 494 | ] 495 | }, 496 | "execution_count": 34, 497 | "metadata": {}, 498 | "output_type": "execute_result" 499 | } 500 | ], 501 | "source": [ 502 | "my_list_10" 503 | ] 504 | }, 505 | { 506 | "cell_type": "code", 507 | "execution_count": 35, 508 | "metadata": {}, 509 | "outputs": [], 510 | "source": [ 511 | "my_list_10.append(\"a\")" 512 | ] 513 | }, 514 | { 515 | "cell_type": "code", 516 | "execution_count": 36, 517 | "metadata": {}, 518 | "outputs": [], 519 | "source": [ 520 | "my_list_10.append(2)" 521 | ] 522 | }, 523 | { 524 | "cell_type": "code", 525 | "execution_count": 37, 526 | "metadata": {}, 527 | "outputs": [], 528 | "source": [ 529 | "my_list_10.append([1,2])" 530 | ] 531 | }, 532 | { 533 | "cell_type": "code", 534 | "execution_count": 38, 535 | "metadata": {}, 536 | "outputs": [ 537 | { 538 | "data": { 539 | "text/plain": [ 540 | "['a', 2, [1, 2]]" 541 | ] 542 | }, 543 | "execution_count": 38, 544 | "metadata": {}, 545 | "output_type": "execute_result" 546 | } 547 | ], 548 | "source": [ 549 | "my_list_10" 550 | ] 551 | }, 552 | { 553 | "cell_type": "code", 554 | "execution_count": null, 555 | "metadata": {}, 556 | "outputs": [], 557 | "source": [] 558 | } 559 | ], 560 | "metadata": { 561 | "kernelspec": { 562 | "display_name": "Python 3", 563 | "language": "python", 564 | "name": "python3" 565 | }, 566 | "language_info": { 567 | "codemirror_mode": { 568 | "name": "ipython", 569 | "version": 3 570 | }, 571 | "file_extension": ".py", 572 | "mimetype": "text/x-python", 573 | "name": "python", 574 | "nbconvert_exporter": "python", 575 | "pygments_lexer": "ipython3", 576 | "version": "3.6.4" 577 | } 578 | }, 579 | "nbformat": 4, 580 | "nbformat_minor": 2 581 | } 582 | -------------------------------------------------------------------------------- /07-Tuple.ipynb: -------------------------------------------------------------------------------- 1 | { 2 | "cells": [ 3 | { 4 | "cell_type": "code", 5 | "execution_count": 1, 6 | "metadata": {}, 7 | "outputs": [], 8 | "source": [ 9 | "my_list = [\"a\",1,\"c\"]" 10 | ] 11 | }, 12 | { 13 | "cell_type": "code", 14 | "execution_count": 3, 15 | "metadata": {}, 16 | "outputs": [], 17 | "source": [ 18 | "my_list[0] = \"b\"" 19 | ] 20 | }, 21 | { 22 | "cell_type": "code", 23 | "execution_count": 4, 24 | "metadata": {}, 25 | "outputs": [ 26 | { 27 | "data": { 28 | "text/plain": [ 29 | "['b', 1, 'c']" 30 | ] 31 | }, 32 | "execution_count": 4, 33 | "metadata": {}, 34 | "output_type": "execute_result" 35 | } 36 | ], 37 | "source": [ 38 | "my_list" 39 | ] 40 | }, 41 | { 42 | "cell_type": "code", 43 | "execution_count": 5, 44 | "metadata": {}, 45 | "outputs": [], 46 | "source": [ 47 | "my_tuple = (\"a\",1,\"c\")" 48 | ] 49 | }, 50 | { 51 | "cell_type": "code", 52 | "execution_count": 6, 53 | "metadata": {}, 54 | "outputs": [ 55 | { 56 | "data": { 57 | "text/plain": [ 58 | "'a'" 59 | ] 60 | }, 61 | "execution_count": 6, 62 | "metadata": {}, 63 | "output_type": "execute_result" 64 | } 65 | ], 66 | "source": [ 67 | "my_tuple[0]" 68 | ] 69 | }, 70 | { 71 | "cell_type": "code", 72 | "execution_count": 8, 73 | "metadata": {}, 74 | "outputs": [], 75 | "source": [ 76 | "#my_tuple[0] = \"b\"" 77 | ] 78 | }, 79 | { 80 | "cell_type": "markdown", 81 | "metadata": {}, 82 | "source": [ 83 | "## immutable" 84 | ] 85 | }, 86 | { 87 | "cell_type": "code", 88 | "execution_count": 9, 89 | "metadata": {}, 90 | "outputs": [], 91 | "source": [ 92 | "#my_tuple[1] = 2" 93 | ] 94 | }, 95 | { 96 | "cell_type": "code", 97 | "execution_count": 11, 98 | "metadata": {}, 99 | "outputs": [ 100 | { 101 | "data": { 102 | "text/plain": [ 103 | "1" 104 | ] 105 | }, 106 | "execution_count": 11, 107 | "metadata": {}, 108 | "output_type": "execute_result" 109 | } 110 | ], 111 | "source": [ 112 | "my_tuple.count(\"a\")" 113 | ] 114 | }, 115 | { 116 | "cell_type": "code", 117 | "execution_count": 12, 118 | "metadata": {}, 119 | "outputs": [], 120 | "source": [ 121 | "my_tuple_2 = (1,1,1,\"a\",\"c\")" 122 | ] 123 | }, 124 | { 125 | "cell_type": "code", 126 | "execution_count": 13, 127 | "metadata": {}, 128 | "outputs": [ 129 | { 130 | "data": { 131 | "text/plain": [ 132 | "3" 133 | ] 134 | }, 135 | "execution_count": 13, 136 | "metadata": {}, 137 | "output_type": "execute_result" 138 | } 139 | ], 140 | "source": [ 141 | "my_tuple_2.count(1)" 142 | ] 143 | }, 144 | { 145 | "cell_type": "code", 146 | "execution_count": 14, 147 | "metadata": {}, 148 | "outputs": [ 149 | { 150 | "data": { 151 | "text/plain": [ 152 | "3" 153 | ] 154 | }, 155 | "execution_count": 14, 156 | "metadata": {}, 157 | "output_type": "execute_result" 158 | } 159 | ], 160 | "source": [ 161 | "my_tuple_2.index(\"a\")" 162 | ] 163 | }, 164 | { 165 | "cell_type": "code", 166 | "execution_count": 15, 167 | "metadata": {}, 168 | "outputs": [ 169 | { 170 | "data": { 171 | "text/plain": [ 172 | "0" 173 | ] 174 | }, 175 | "execution_count": 15, 176 | "metadata": {}, 177 | "output_type": "execute_result" 178 | } 179 | ], 180 | "source": [ 181 | "my_tuple_2.index(1)" 182 | ] 183 | }, 184 | { 185 | "cell_type": "code", 186 | "execution_count": null, 187 | "metadata": {}, 188 | "outputs": [], 189 | "source": [] 190 | } 191 | ], 192 | "metadata": { 193 | "kernelspec": { 194 | "display_name": "Python 3", 195 | "language": "python", 196 | "name": "python3" 197 | }, 198 | "language_info": { 199 | "codemirror_mode": { 200 | "name": "ipython", 201 | "version": 3 202 | }, 203 | "file_extension": ".py", 204 | "mimetype": "text/x-python", 205 | "name": "python", 206 | "nbconvert_exporter": "python", 207 | "pygments_lexer": "ipython3", 208 | "version": "3.6.4" 209 | } 210 | }, 211 | "nbformat": 4, 212 | "nbformat_minor": 2 213 | } 214 | -------------------------------------------------------------------------------- /08-Boolean.ipynb: -------------------------------------------------------------------------------- 1 | { 2 | "cells": [ 3 | { 4 | "cell_type": "code", 5 | "execution_count": 1, 6 | "metadata": {}, 7 | "outputs": [ 8 | { 9 | "data": { 10 | "text/plain": [ 11 | "True" 12 | ] 13 | }, 14 | "execution_count": 1, 15 | "metadata": {}, 16 | "output_type": "execute_result" 17 | } 18 | ], 19 | "source": [ 20 | "True" 21 | ] 22 | }, 23 | { 24 | "cell_type": "code", 25 | "execution_count": 2, 26 | "metadata": {}, 27 | "outputs": [ 28 | { 29 | "data": { 30 | "text/plain": [ 31 | "False" 32 | ] 33 | }, 34 | "execution_count": 2, 35 | "metadata": {}, 36 | "output_type": "execute_result" 37 | } 38 | ], 39 | "source": [ 40 | "False" 41 | ] 42 | }, 43 | { 44 | "cell_type": "code", 45 | "execution_count": 4, 46 | "metadata": {}, 47 | "outputs": [], 48 | "source": [ 49 | "my_boolean = True" 50 | ] 51 | }, 52 | { 53 | "cell_type": "code", 54 | "execution_count": 5, 55 | "metadata": {}, 56 | "outputs": [], 57 | "source": [ 58 | "is_dead = False" 59 | ] 60 | }, 61 | { 62 | "cell_type": "code", 63 | "execution_count": 6, 64 | "metadata": {}, 65 | "outputs": [ 66 | { 67 | "data": { 68 | "text/plain": [ 69 | "True" 70 | ] 71 | }, 72 | "execution_count": 6, 73 | "metadata": {}, 74 | "output_type": "execute_result" 75 | } 76 | ], 77 | "source": [ 78 | "5 > 3" 79 | ] 80 | }, 81 | { 82 | "cell_type": "code", 83 | "execution_count": 7, 84 | "metadata": {}, 85 | "outputs": [ 86 | { 87 | "data": { 88 | "text/plain": [ 89 | "8" 90 | ] 91 | }, 92 | "execution_count": 7, 93 | "metadata": {}, 94 | "output_type": "execute_result" 95 | } 96 | ], 97 | "source": [ 98 | "5 + 3" 99 | ] 100 | }, 101 | { 102 | "cell_type": "code", 103 | "execution_count": 8, 104 | "metadata": {}, 105 | "outputs": [ 106 | { 107 | "data": { 108 | "text/plain": [ 109 | "False" 110 | ] 111 | }, 112 | "execution_count": 8, 113 | "metadata": {}, 114 | "output_type": "execute_result" 115 | } 116 | ], 117 | "source": [ 118 | "3 > 5" 119 | ] 120 | }, 121 | { 122 | "cell_type": "code", 123 | "execution_count": 9, 124 | "metadata": {}, 125 | "outputs": [], 126 | "source": [ 127 | "x = 5" 128 | ] 129 | }, 130 | { 131 | "cell_type": "code", 132 | "execution_count": 10, 133 | "metadata": {}, 134 | "outputs": [ 135 | { 136 | "name": "stdout", 137 | "output_type": "stream", 138 | "text": [ 139 | "y: 6\n" 140 | ] 141 | } 142 | ], 143 | "source": [ 144 | "y = input(\"y: \")" 145 | ] 146 | }, 147 | { 148 | "cell_type": "code", 149 | "execution_count": 11, 150 | "metadata": {}, 151 | "outputs": [ 152 | { 153 | "data": { 154 | "text/plain": [ 155 | "str" 156 | ] 157 | }, 158 | "execution_count": 11, 159 | "metadata": {}, 160 | "output_type": "execute_result" 161 | } 162 | ], 163 | "source": [ 164 | "type(y)" 165 | ] 166 | }, 167 | { 168 | "cell_type": "code", 169 | "execution_count": 12, 170 | "metadata": {}, 171 | "outputs": [], 172 | "source": [ 173 | "y_int = int(y)" 174 | ] 175 | }, 176 | { 177 | "cell_type": "code", 178 | "execution_count": 13, 179 | "metadata": {}, 180 | "outputs": [ 181 | { 182 | "data": { 183 | "text/plain": [ 184 | "int" 185 | ] 186 | }, 187 | "execution_count": 13, 188 | "metadata": {}, 189 | "output_type": "execute_result" 190 | } 191 | ], 192 | "source": [ 193 | "type(y_int)" 194 | ] 195 | }, 196 | { 197 | "cell_type": "code", 198 | "execution_count": 14, 199 | "metadata": {}, 200 | "outputs": [ 201 | { 202 | "data": { 203 | "text/plain": [ 204 | "6" 205 | ] 206 | }, 207 | "execution_count": 14, 208 | "metadata": {}, 209 | "output_type": "execute_result" 210 | } 211 | ], 212 | "source": [ 213 | "y_int" 214 | ] 215 | }, 216 | { 217 | "cell_type": "code", 218 | "execution_count": 15, 219 | "metadata": {}, 220 | "outputs": [ 221 | { 222 | "data": { 223 | "text/plain": [ 224 | "True" 225 | ] 226 | }, 227 | "execution_count": 15, 228 | "metadata": {}, 229 | "output_type": "execute_result" 230 | } 231 | ], 232 | "source": [ 233 | "y_int > x" 234 | ] 235 | }, 236 | { 237 | "cell_type": "code", 238 | "execution_count": null, 239 | "metadata": {}, 240 | "outputs": [], 241 | "source": [] 242 | } 243 | ], 244 | "metadata": { 245 | "kernelspec": { 246 | "display_name": "Python 3", 247 | "language": "python", 248 | "name": "python3" 249 | }, 250 | "language_info": { 251 | "codemirror_mode": { 252 | "name": "ipython", 253 | "version": 3 254 | }, 255 | "file_extension": ".py", 256 | "mimetype": "text/x-python", 257 | "name": "python", 258 | "nbconvert_exporter": "python", 259 | "pygments_lexer": "ipython3", 260 | "version": "3.6.4" 261 | } 262 | }, 263 | "nbformat": 4, 264 | "nbformat_minor": 2 265 | } 266 | -------------------------------------------------------------------------------- /09-Exam 1.ipynb: -------------------------------------------------------------------------------- 1 | { 2 | "cells": [ 3 | { 4 | "cell_type": "markdown", 5 | "metadata": {}, 6 | "source": [ 7 | "## String" 8 | ] 9 | }, 10 | { 11 | "cell_type": "code", 12 | "execution_count": 1, 13 | "metadata": {}, 14 | "outputs": [], 15 | "source": [ 16 | "# 1) Aşağıdaki String'in 5. harfini my_letter isimli bir değişkene atayınız." 17 | ] 18 | }, 19 | { 20 | "cell_type": "code", 21 | "execution_count": 6, 22 | "metadata": {}, 23 | "outputs": [], 24 | "source": [ 25 | "my_string = \"James Hetfield\"" 26 | ] 27 | }, 28 | { 29 | "cell_type": "code", 30 | "execution_count": null, 31 | "metadata": {}, 32 | "outputs": [], 33 | "source": [ 34 | "# Cevap 1)" 35 | ] 36 | }, 37 | { 38 | "cell_type": "code", 39 | "execution_count": 7, 40 | "metadata": {}, 41 | "outputs": [], 42 | "source": [ 43 | "# Aşağıdaki String'in 5. ve 8. karakteri arasındaki tüm harflerini yazdırınız (5 ve 8 dahil)" 44 | ] 45 | }, 46 | { 47 | "cell_type": "code", 48 | "execution_count": 5, 49 | "metadata": {}, 50 | "outputs": [], 51 | "source": [ 52 | "my_new_string = \"QuentinTarantino\"" 53 | ] 54 | }, 55 | { 56 | "cell_type": "code", 57 | "execution_count": 8, 58 | "metadata": {}, 59 | "outputs": [], 60 | "source": [ 61 | "# Cevap 2)" 62 | ] 63 | }, 64 | { 65 | "cell_type": "code", 66 | "execution_count": 9, 67 | "metadata": {}, 68 | "outputs": [], 69 | "source": [ 70 | "# Aşağıdaki String'i kod ile tersten yazın" 71 | ] 72 | }, 73 | { 74 | "cell_type": "code", 75 | "execution_count": 10, 76 | "metadata": {}, 77 | "outputs": [], 78 | "source": [ 79 | "my_last_string = \"Afyonkarahisarlılaştıramadıklarımızdanmısınız\"" 80 | ] 81 | }, 82 | { 83 | "cell_type": "code", 84 | "execution_count": 11, 85 | "metadata": {}, 86 | "outputs": [], 87 | "source": [ 88 | "# Cevap 3)" 89 | ] 90 | }, 91 | { 92 | "cell_type": "markdown", 93 | "metadata": {}, 94 | "source": [ 95 | "## Integer & Float" 96 | ] 97 | }, 98 | { 99 | "cell_type": "code", 100 | "execution_count": 12, 101 | "metadata": {}, 102 | "outputs": [], 103 | "source": [ 104 | "# 1) Aşağıdaki işlemin sonucu hangi veri tipinde olacaktır?" 105 | ] 106 | }, 107 | { 108 | "cell_type": "markdown", 109 | "metadata": {}, 110 | "source": [ 111 | "3 + 10.2 + 50" 112 | ] 113 | }, 114 | { 115 | "cell_type": "code", 116 | "execution_count": 13, 117 | "metadata": {}, 118 | "outputs": [], 119 | "source": [ 120 | "# Cevap 1)" 121 | ] 122 | }, 123 | { 124 | "cell_type": "code", 125 | "execution_count": 14, 126 | "metadata": {}, 127 | "outputs": [], 128 | "source": [ 129 | "# 2) Aşağıdaki işlemin sonucu kaçtır?" 130 | ] 131 | }, 132 | { 133 | "cell_type": "markdown", 134 | "metadata": {}, 135 | "source": [ 136 | "5 + 8 * 12" 137 | ] 138 | }, 139 | { 140 | "cell_type": "code", 141 | "execution_count": 15, 142 | "metadata": {}, 143 | "outputs": [], 144 | "source": [ 145 | "# Cevap 2)" 146 | ] 147 | }, 148 | { 149 | "cell_type": "markdown", 150 | "metadata": {}, 151 | "source": [ 152 | "## List & Dictionary & Set" 153 | ] 154 | }, 155 | { 156 | "cell_type": "code", 157 | "execution_count": 16, 158 | "metadata": {}, 159 | "outputs": [], 160 | "source": [ 161 | "# 1) Bu listeyi 3 farklı yoldan oluşturunuz: [1,2,\"a\"]" 162 | ] 163 | }, 164 | { 165 | "cell_type": "code", 166 | "execution_count": 17, 167 | "metadata": {}, 168 | "outputs": [], 169 | "source": [ 170 | "# Cevap 1.a)" 171 | ] 172 | }, 173 | { 174 | "cell_type": "code", 175 | "execution_count": 18, 176 | "metadata": {}, 177 | "outputs": [], 178 | "source": [ 179 | "# Cevap 1.b)" 180 | ] 181 | }, 182 | { 183 | "cell_type": "code", 184 | "execution_count": 19, 185 | "metadata": {}, 186 | "outputs": [], 187 | "source": [ 188 | "# Cevap 1.c)" 189 | ] 190 | }, 191 | { 192 | "cell_type": "code", 193 | "execution_count": 20, 194 | "metadata": {}, 195 | "outputs": [], 196 | "source": [ 197 | "# 2) Aşağıdaki \"a\"'yı tek satırda alınız:" 198 | ] 199 | }, 200 | { 201 | "cell_type": "code", 202 | "execution_count": 21, 203 | "metadata": {}, 204 | "outputs": [], 205 | "source": [ 206 | "my_list = [1,4,[2,3,\"a\"]]" 207 | ] 208 | }, 209 | { 210 | "cell_type": "code", 211 | "execution_count": 22, 212 | "metadata": {}, 213 | "outputs": [], 214 | "source": [ 215 | "# Cevap 2)" 216 | ] 217 | }, 218 | { 219 | "cell_type": "code", 220 | "execution_count": 23, 221 | "metadata": {}, 222 | "outputs": [], 223 | "source": [ 224 | "# 3) Aşağıdaki \"b\"'yi tek satırda alınız:" 225 | ] 226 | }, 227 | { 228 | "cell_type": "code", 229 | "execution_count": null, 230 | "metadata": {}, 231 | "outputs": [], 232 | "source": [ 233 | "my_dictionary = {\"k1\":2, \"kk\":[4,{\"kkkk\":\"b\"}]}" 234 | ] 235 | }, 236 | { 237 | "cell_type": "code", 238 | "execution_count": 25, 239 | "metadata": {}, 240 | "outputs": [], 241 | "source": [ 242 | "# Cevap 3)" 243 | ] 244 | }, 245 | { 246 | "cell_type": "code", 247 | "execution_count": 26, 248 | "metadata": {}, 249 | "outputs": [], 250 | "source": [ 251 | "# 4) Aşağıdaki liste set'e çevirilince hangi değerler içinde kalacaktır?" 252 | ] 253 | }, 254 | { 255 | "cell_type": "code", 256 | "execution_count": 27, 257 | "metadata": {}, 258 | "outputs": [], 259 | "source": [ 260 | "my_list_to_be_set = [11,12,22,33,11,22,45,32,21,22,33,45]" 261 | ] 262 | }, 263 | { 264 | "cell_type": "code", 265 | "execution_count": 28, 266 | "metadata": {}, 267 | "outputs": [], 268 | "source": [ 269 | "# Cevap 4)" 270 | ] 271 | }, 272 | { 273 | "cell_type": "markdown", 274 | "metadata": {}, 275 | "source": [ 276 | "## Boolean" 277 | ] 278 | }, 279 | { 280 | "cell_type": "code", 281 | "execution_count": 29, 282 | "metadata": {}, 283 | "outputs": [], 284 | "source": [ 285 | "# 1) Aşağıdaki ifadenin sonucu ne olacaktır?" 286 | ] 287 | }, 288 | { 289 | "cell_type": "code", 290 | "execution_count": 30, 291 | "metadata": {}, 292 | "outputs": [], 293 | "source": [ 294 | "x = 40 * 5 + 3" 295 | ] 296 | }, 297 | { 298 | "cell_type": "code", 299 | "execution_count": 31, 300 | "metadata": {}, 301 | "outputs": [], 302 | "source": [ 303 | "y = 208 - 2 * 4" 304 | ] 305 | }, 306 | { 307 | "cell_type": "markdown", 308 | "metadata": {}, 309 | "source": [ 310 | "x > y" 311 | ] 312 | }, 313 | { 314 | "cell_type": "code", 315 | "execution_count": 32, 316 | "metadata": {}, 317 | "outputs": [], 318 | "source": [ 319 | "# Cevap 1)" 320 | ] 321 | }, 322 | { 323 | "cell_type": "code", 324 | "execution_count": 33, 325 | "metadata": {}, 326 | "outputs": [], 327 | "source": [ 328 | "# 2) Aşağıdaki ifadenin sonucu ne olacaktır?" 329 | ] 330 | }, 331 | { 332 | "cell_type": "code", 333 | "execution_count": 34, 334 | "metadata": {}, 335 | "outputs": [], 336 | "source": [ 337 | "a = 40 * (4 - 2)" 338 | ] 339 | }, 340 | { 341 | "cell_type": "code", 342 | "execution_count": 35, 343 | "metadata": {}, 344 | "outputs": [], 345 | "source": [ 346 | "b = 80 - 2 * -5" 347 | ] 348 | }, 349 | { 350 | "cell_type": "markdown", 351 | "metadata": {}, 352 | "source": [ 353 | "a > b" 354 | ] 355 | }, 356 | { 357 | "cell_type": "code", 358 | "execution_count": 36, 359 | "metadata": {}, 360 | "outputs": [], 361 | "source": [ 362 | "# Cevap 2)" 363 | ] 364 | }, 365 | { 366 | "cell_type": "code", 367 | "execution_count": null, 368 | "metadata": {}, 369 | "outputs": [], 370 | "source": [] 371 | } 372 | ], 373 | "metadata": { 374 | "kernelspec": { 375 | "display_name": "Python 3", 376 | "language": "python", 377 | "name": "python3" 378 | }, 379 | "language_info": { 380 | "codemirror_mode": { 381 | "name": "ipython", 382 | "version": 3 383 | }, 384 | "file_extension": ".py", 385 | "mimetype": "text/x-python", 386 | "name": "python", 387 | "nbconvert_exporter": "python", 388 | "pygments_lexer": "ipython3", 389 | "version": "3.6.4" 390 | } 391 | }, 392 | "nbformat": 4, 393 | "nbformat_minor": 2 394 | } 395 | -------------------------------------------------------------------------------- /10-Exam 1 Solutions.ipynb: -------------------------------------------------------------------------------- 1 | { 2 | "cells": [ 3 | { 4 | "cell_type": "markdown", 5 | "metadata": {}, 6 | "source": [ 7 | "## String" 8 | ] 9 | }, 10 | { 11 | "cell_type": "code", 12 | "execution_count": 2, 13 | "metadata": {}, 14 | "outputs": [], 15 | "source": [ 16 | "# 1) Aşağıdaki String'in 5. harfini my_letter isimli bir değişkene atayınız." 17 | ] 18 | }, 19 | { 20 | "cell_type": "code", 21 | "execution_count": 3, 22 | "metadata": {}, 23 | "outputs": [], 24 | "source": [ 25 | "my_string = \"James Hetfield\"" 26 | ] 27 | }, 28 | { 29 | "cell_type": "code", 30 | "execution_count": 4, 31 | "metadata": {}, 32 | "outputs": [ 33 | { 34 | "data": { 35 | "text/plain": [ 36 | "'s'" 37 | ] 38 | }, 39 | "execution_count": 4, 40 | "metadata": {}, 41 | "output_type": "execute_result" 42 | } 43 | ], 44 | "source": [ 45 | "my_string[4]" 46 | ] 47 | }, 48 | { 49 | "cell_type": "code", 50 | "execution_count": 5, 51 | "metadata": {}, 52 | "outputs": [], 53 | "source": [ 54 | "# Aşağıdaki String'in 5. ve 8. karakteri arasındaki tüm harflerini yazdırınız (5 ve 8 dahil)" 55 | ] 56 | }, 57 | { 58 | "cell_type": "code", 59 | "execution_count": 6, 60 | "metadata": {}, 61 | "outputs": [], 62 | "source": [ 63 | "my_new_string = \"QuentinTarantino\"" 64 | ] 65 | }, 66 | { 67 | "cell_type": "code", 68 | "execution_count": 39, 69 | "metadata": {}, 70 | "outputs": [ 71 | { 72 | "data": { 73 | "text/plain": [ 74 | "'tinT'" 75 | ] 76 | }, 77 | "execution_count": 39, 78 | "metadata": {}, 79 | "output_type": "execute_result" 80 | } 81 | ], 82 | "source": [ 83 | "my_new_string[4:8]" 84 | ] 85 | }, 86 | { 87 | "cell_type": "code", 88 | "execution_count": 8, 89 | "metadata": {}, 90 | "outputs": [], 91 | "source": [ 92 | "# Aşağıdaki String'i kod ile tersten yazın" 93 | ] 94 | }, 95 | { 96 | "cell_type": "code", 97 | "execution_count": 9, 98 | "metadata": {}, 99 | "outputs": [], 100 | "source": [ 101 | "my_last_string = \"Afyonkarahisarlılaştıramadıklarımızdanmısınız\"" 102 | ] 103 | }, 104 | { 105 | "cell_type": "code", 106 | "execution_count": 40, 107 | "metadata": {}, 108 | "outputs": [ 109 | { 110 | "data": { 111 | "text/plain": [ 112 | "'zınısımnadzımıralkıdamarıtşalılrasiharaknoyfA'" 113 | ] 114 | }, 115 | "execution_count": 40, 116 | "metadata": {}, 117 | "output_type": "execute_result" 118 | } 119 | ], 120 | "source": [ 121 | "my_last_string[::-1]" 122 | ] 123 | }, 124 | { 125 | "cell_type": "markdown", 126 | "metadata": {}, 127 | "source": [ 128 | "## Integer & Float" 129 | ] 130 | }, 131 | { 132 | "cell_type": "code", 133 | "execution_count": 11, 134 | "metadata": {}, 135 | "outputs": [], 136 | "source": [ 137 | "# 1) Aşağıdaki işlemin sonucu hangi veri tipinde olacaktır?" 138 | ] 139 | }, 140 | { 141 | "cell_type": "markdown", 142 | "metadata": {}, 143 | "source": [ 144 | "3 + 10.2 + 50" 145 | ] 146 | }, 147 | { 148 | "cell_type": "code", 149 | "execution_count": null, 150 | "metadata": {}, 151 | "outputs": [], 152 | "source": [ 153 | "number = 3 + 10.2 + 50" 154 | ] 155 | }, 156 | { 157 | "cell_type": "code", 158 | "execution_count": 42, 159 | "metadata": {}, 160 | "outputs": [ 161 | { 162 | "data": { 163 | "text/plain": [ 164 | "float" 165 | ] 166 | }, 167 | "execution_count": 42, 168 | "metadata": {}, 169 | "output_type": "execute_result" 170 | } 171 | ], 172 | "source": [ 173 | "type(number)" 174 | ] 175 | }, 176 | { 177 | "cell_type": "code", 178 | "execution_count": 13, 179 | "metadata": {}, 180 | "outputs": [], 181 | "source": [ 182 | "# 2) Aşağıdaki işlemin sonucu kaçtır?" 183 | ] 184 | }, 185 | { 186 | "cell_type": "markdown", 187 | "metadata": {}, 188 | "source": [ 189 | "5 + 8 * 12" 190 | ] 191 | }, 192 | { 193 | "cell_type": "code", 194 | "execution_count": 43, 195 | "metadata": {}, 196 | "outputs": [ 197 | { 198 | "data": { 199 | "text/plain": [ 200 | "101" 201 | ] 202 | }, 203 | "execution_count": 43, 204 | "metadata": {}, 205 | "output_type": "execute_result" 206 | } 207 | ], 208 | "source": [ 209 | "5 + 8 * 12" 210 | ] 211 | }, 212 | { 213 | "cell_type": "markdown", 214 | "metadata": {}, 215 | "source": [ 216 | "## List & Dictionary & Set" 217 | ] 218 | }, 219 | { 220 | "cell_type": "code", 221 | "execution_count": 15, 222 | "metadata": {}, 223 | "outputs": [], 224 | "source": [ 225 | "# 1) Bu listeyi 3 farklı yoldan oluşturunuz: [1,2,\"a\"]" 226 | ] 227 | }, 228 | { 229 | "cell_type": "code", 230 | "execution_count": 44, 231 | "metadata": {}, 232 | "outputs": [], 233 | "source": [ 234 | "my_list_1 = [1,2,\"a\"]" 235 | ] 236 | }, 237 | { 238 | "cell_type": "code", 239 | "execution_count": 45, 240 | "metadata": {}, 241 | "outputs": [], 242 | "source": [ 243 | "my_list_2 = []" 244 | ] 245 | }, 246 | { 247 | "cell_type": "code", 248 | "execution_count": 46, 249 | "metadata": {}, 250 | "outputs": [], 251 | "source": [ 252 | "my_list_2.append(1)" 253 | ] 254 | }, 255 | { 256 | "cell_type": "code", 257 | "execution_count": 47, 258 | "metadata": {}, 259 | "outputs": [], 260 | "source": [ 261 | "my_list_2.append(2)" 262 | ] 263 | }, 264 | { 265 | "cell_type": "code", 266 | "execution_count": 48, 267 | "metadata": {}, 268 | "outputs": [], 269 | "source": [ 270 | "my_list_2.append(\"a\")" 271 | ] 272 | }, 273 | { 274 | "cell_type": "code", 275 | "execution_count": 49, 276 | "metadata": {}, 277 | "outputs": [ 278 | { 279 | "data": { 280 | "text/plain": [ 281 | "[1, 2, 'a']" 282 | ] 283 | }, 284 | "execution_count": 49, 285 | "metadata": {}, 286 | "output_type": "execute_result" 287 | } 288 | ], 289 | "source": [ 290 | "my_list_2" 291 | ] 292 | }, 293 | { 294 | "cell_type": "code", 295 | "execution_count": 50, 296 | "metadata": {}, 297 | "outputs": [], 298 | "source": [ 299 | "my_list_3 = list()" 300 | ] 301 | }, 302 | { 303 | "cell_type": "code", 304 | "execution_count": 51, 305 | "metadata": {}, 306 | "outputs": [], 307 | "source": [ 308 | "my_list_3.append(1)" 309 | ] 310 | }, 311 | { 312 | "cell_type": "code", 313 | "execution_count": 52, 314 | "metadata": {}, 315 | "outputs": [], 316 | "source": [ 317 | "my_list_3.append(2)" 318 | ] 319 | }, 320 | { 321 | "cell_type": "code", 322 | "execution_count": 53, 323 | "metadata": {}, 324 | "outputs": [], 325 | "source": [ 326 | "my_list_3.append(\"a\")" 327 | ] 328 | }, 329 | { 330 | "cell_type": "code", 331 | "execution_count": 54, 332 | "metadata": {}, 333 | "outputs": [ 334 | { 335 | "data": { 336 | "text/plain": [ 337 | "[1, 2, 'a']" 338 | ] 339 | }, 340 | "execution_count": 54, 341 | "metadata": {}, 342 | "output_type": "execute_result" 343 | } 344 | ], 345 | "source": [ 346 | "my_list_3" 347 | ] 348 | }, 349 | { 350 | "cell_type": "code", 351 | "execution_count": 19, 352 | "metadata": {}, 353 | "outputs": [], 354 | "source": [ 355 | "# 2) Aşağıdaki \"a\"'yı tek satırda alınız:" 356 | ] 357 | }, 358 | { 359 | "cell_type": "code", 360 | "execution_count": 20, 361 | "metadata": {}, 362 | "outputs": [], 363 | "source": [ 364 | "my_list = [1,4,[2,3,\"a\"]]" 365 | ] 366 | }, 367 | { 368 | "cell_type": "code", 369 | "execution_count": 55, 370 | "metadata": {}, 371 | "outputs": [ 372 | { 373 | "data": { 374 | "text/plain": [ 375 | "'a'" 376 | ] 377 | }, 378 | "execution_count": 55, 379 | "metadata": {}, 380 | "output_type": "execute_result" 381 | } 382 | ], 383 | "source": [ 384 | "my_list[2][2]" 385 | ] 386 | }, 387 | { 388 | "cell_type": "code", 389 | "execution_count": 22, 390 | "metadata": {}, 391 | "outputs": [], 392 | "source": [ 393 | "# 3) Aşağıdaki \"b\"'yi tek satırda alınız:" 394 | ] 395 | }, 396 | { 397 | "cell_type": "code", 398 | "execution_count": 23, 399 | "metadata": {}, 400 | "outputs": [], 401 | "source": [ 402 | "my_dictionary = {\"k1\":2, \"kk\":[4,{\"kkkk\":\"b\"}]}" 403 | ] 404 | }, 405 | { 406 | "cell_type": "code", 407 | "execution_count": 56, 408 | "metadata": {}, 409 | "outputs": [ 410 | { 411 | "data": { 412 | "text/plain": [ 413 | "'b'" 414 | ] 415 | }, 416 | "execution_count": 56, 417 | "metadata": {}, 418 | "output_type": "execute_result" 419 | } 420 | ], 421 | "source": [ 422 | "my_dictionary[\"kk\"][1][\"kkkk\"]" 423 | ] 424 | }, 425 | { 426 | "cell_type": "code", 427 | "execution_count": 25, 428 | "metadata": {}, 429 | "outputs": [], 430 | "source": [ 431 | "# 4) Aşağıdaki liste set'e çevirilince hangi değerler içinde kalacaktır?" 432 | ] 433 | }, 434 | { 435 | "cell_type": "code", 436 | "execution_count": 26, 437 | "metadata": {}, 438 | "outputs": [], 439 | "source": [ 440 | "my_list_to_be_set = [11,12,22,33,11,22,45,32,21,22,33,45]" 441 | ] 442 | }, 443 | { 444 | "cell_type": "code", 445 | "execution_count": 58, 446 | "metadata": {}, 447 | "outputs": [], 448 | "source": [ 449 | "my_new_set = set(my_list_to_be_set)" 450 | ] 451 | }, 452 | { 453 | "cell_type": "code", 454 | "execution_count": 60, 455 | "metadata": {}, 456 | "outputs": [ 457 | { 458 | "data": { 459 | "text/plain": [ 460 | "{11, 12, 21, 22, 32, 33, 45}" 461 | ] 462 | }, 463 | "execution_count": 60, 464 | "metadata": {}, 465 | "output_type": "execute_result" 466 | } 467 | ], 468 | "source": [ 469 | "my_new_set" 470 | ] 471 | }, 472 | { 473 | "cell_type": "markdown", 474 | "metadata": {}, 475 | "source": [ 476 | "## Boolean" 477 | ] 478 | }, 479 | { 480 | "cell_type": "code", 481 | "execution_count": 28, 482 | "metadata": {}, 483 | "outputs": [], 484 | "source": [ 485 | "# 1) Aşağıdaki ifadenin sonucu ne olacaktır?" 486 | ] 487 | }, 488 | { 489 | "cell_type": "code", 490 | "execution_count": 29, 491 | "metadata": {}, 492 | "outputs": [], 493 | "source": [ 494 | "x = 40 * 5 + 3" 495 | ] 496 | }, 497 | { 498 | "cell_type": "code", 499 | "execution_count": 30, 500 | "metadata": {}, 501 | "outputs": [], 502 | "source": [ 503 | "y = 208 - 2 * 4" 504 | ] 505 | }, 506 | { 507 | "cell_type": "markdown", 508 | "metadata": {}, 509 | "source": [ 510 | "x > y" 511 | ] 512 | }, 513 | { 514 | "cell_type": "code", 515 | "execution_count": 61, 516 | "metadata": {}, 517 | "outputs": [ 518 | { 519 | "data": { 520 | "text/plain": [ 521 | "True" 522 | ] 523 | }, 524 | "execution_count": 61, 525 | "metadata": {}, 526 | "output_type": "execute_result" 527 | } 528 | ], 529 | "source": [ 530 | "x > y" 531 | ] 532 | }, 533 | { 534 | "cell_type": "code", 535 | "execution_count": 32, 536 | "metadata": {}, 537 | "outputs": [], 538 | "source": [ 539 | "# 2) Aşağıdaki ifadenin sonucu ne olacaktır?" 540 | ] 541 | }, 542 | { 543 | "cell_type": "code", 544 | "execution_count": 33, 545 | "metadata": {}, 546 | "outputs": [], 547 | "source": [ 548 | "a = 40 * (4 - 2)" 549 | ] 550 | }, 551 | { 552 | "cell_type": "code", 553 | "execution_count": 34, 554 | "metadata": {}, 555 | "outputs": [], 556 | "source": [ 557 | "b = 80 - 2 * -5" 558 | ] 559 | }, 560 | { 561 | "cell_type": "markdown", 562 | "metadata": {}, 563 | "source": [ 564 | "a > b" 565 | ] 566 | }, 567 | { 568 | "cell_type": "code", 569 | "execution_count": 35, 570 | "metadata": {}, 571 | "outputs": [], 572 | "source": [ 573 | "# Cevap 2)" 574 | ] 575 | }, 576 | { 577 | "cell_type": "code", 578 | "execution_count": 62, 579 | "metadata": {}, 580 | "outputs": [ 581 | { 582 | "data": { 583 | "text/plain": [ 584 | "False" 585 | ] 586 | }, 587 | "execution_count": 62, 588 | "metadata": {}, 589 | "output_type": "execute_result" 590 | } 591 | ], 592 | "source": [ 593 | "a > b" 594 | ] 595 | }, 596 | { 597 | "cell_type": "code", 598 | "execution_count": 63, 599 | "metadata": {}, 600 | "outputs": [ 601 | { 602 | "data": { 603 | "text/plain": [ 604 | "80" 605 | ] 606 | }, 607 | "execution_count": 63, 608 | "metadata": {}, 609 | "output_type": "execute_result" 610 | } 611 | ], 612 | "source": [ 613 | "a" 614 | ] 615 | }, 616 | { 617 | "cell_type": "code", 618 | "execution_count": 64, 619 | "metadata": {}, 620 | "outputs": [ 621 | { 622 | "data": { 623 | "text/plain": [ 624 | "90" 625 | ] 626 | }, 627 | "execution_count": 64, 628 | "metadata": {}, 629 | "output_type": "execute_result" 630 | } 631 | ], 632 | "source": [ 633 | "b" 634 | ] 635 | }, 636 | { 637 | "cell_type": "code", 638 | "execution_count": null, 639 | "metadata": {}, 640 | "outputs": [], 641 | "source": [] 642 | } 643 | ], 644 | "metadata": { 645 | "kernelspec": { 646 | "display_name": "Python 3", 647 | "language": "python", 648 | "name": "python3" 649 | }, 650 | "language_info": { 651 | "codemirror_mode": { 652 | "name": "ipython", 653 | "version": 3 654 | }, 655 | "file_extension": ".py", 656 | "mimetype": "text/x-python", 657 | "name": "python", 658 | "nbconvert_exporter": "python", 659 | "pygments_lexer": "ipython3", 660 | "version": "3.6.4" 661 | } 662 | }, 663 | "nbformat": 4, 664 | "nbformat_minor": 2 665 | } 666 | -------------------------------------------------------------------------------- /11-Comparison.ipynb: -------------------------------------------------------------------------------- 1 | { 2 | "cells": [ 3 | { 4 | "cell_type": "code", 5 | "execution_count": 1, 6 | "metadata": {}, 7 | "outputs": [], 8 | "source": [ 9 | "x = 5" 10 | ] 11 | }, 12 | { 13 | "cell_type": "code", 14 | "execution_count": 2, 15 | "metadata": {}, 16 | "outputs": [], 17 | "source": [ 18 | "y = 4" 19 | ] 20 | }, 21 | { 22 | "cell_type": "code", 23 | "execution_count": 3, 24 | "metadata": {}, 25 | "outputs": [ 26 | { 27 | "data": { 28 | "text/plain": [ 29 | "True" 30 | ] 31 | }, 32 | "execution_count": 3, 33 | "metadata": {}, 34 | "output_type": "execute_result" 35 | } 36 | ], 37 | "source": [ 38 | "x > y" 39 | ] 40 | }, 41 | { 42 | "cell_type": "code", 43 | "execution_count": 4, 44 | "metadata": {}, 45 | "outputs": [ 46 | { 47 | "data": { 48 | "text/plain": [ 49 | "False" 50 | ] 51 | }, 52 | "execution_count": 4, 53 | "metadata": {}, 54 | "output_type": "execute_result" 55 | } 56 | ], 57 | "source": [ 58 | "x < y" 59 | ] 60 | }, 61 | { 62 | "cell_type": "code", 63 | "execution_count": 5, 64 | "metadata": {}, 65 | "outputs": [ 66 | { 67 | "data": { 68 | "text/plain": [ 69 | "True" 70 | ] 71 | }, 72 | "execution_count": 5, 73 | "metadata": {}, 74 | "output_type": "execute_result" 75 | } 76 | ], 77 | "source": [ 78 | "x >= y" 79 | ] 80 | }, 81 | { 82 | "cell_type": "code", 83 | "execution_count": 6, 84 | "metadata": {}, 85 | "outputs": [ 86 | { 87 | "data": { 88 | "text/plain": [ 89 | "True" 90 | ] 91 | }, 92 | "execution_count": 6, 93 | "metadata": {}, 94 | "output_type": "execute_result" 95 | } 96 | ], 97 | "source": [ 98 | "x >= 5" 99 | ] 100 | }, 101 | { 102 | "cell_type": "code", 103 | "execution_count": 7, 104 | "metadata": {}, 105 | "outputs": [ 106 | { 107 | "data": { 108 | "text/plain": [ 109 | "True" 110 | ] 111 | }, 112 | "execution_count": 7, 113 | "metadata": {}, 114 | "output_type": "execute_result" 115 | } 116 | ], 117 | "source": [ 118 | "x>=5.0" 119 | ] 120 | }, 121 | { 122 | "cell_type": "code", 123 | "execution_count": 8, 124 | "metadata": {}, 125 | "outputs": [ 126 | { 127 | "data": { 128 | "text/plain": [ 129 | "False" 130 | ] 131 | }, 132 | "execution_count": 8, 133 | "metadata": {}, 134 | "output_type": "execute_result" 135 | } 136 | ], 137 | "source": [ 138 | "x>=5.1" 139 | ] 140 | }, 141 | { 142 | "cell_type": "code", 143 | "execution_count": 9, 144 | "metadata": {}, 145 | "outputs": [], 146 | "source": [ 147 | "x = y" 148 | ] 149 | }, 150 | { 151 | "cell_type": "code", 152 | "execution_count": 10, 153 | "metadata": {}, 154 | "outputs": [ 155 | { 156 | "data": { 157 | "text/plain": [ 158 | "4" 159 | ] 160 | }, 161 | "execution_count": 10, 162 | "metadata": {}, 163 | "output_type": "execute_result" 164 | } 165 | ], 166 | "source": [ 167 | "x" 168 | ] 169 | }, 170 | { 171 | "cell_type": "code", 172 | "execution_count": 11, 173 | "metadata": {}, 174 | "outputs": [ 175 | { 176 | "data": { 177 | "text/plain": [ 178 | "4" 179 | ] 180 | }, 181 | "execution_count": 11, 182 | "metadata": {}, 183 | "output_type": "execute_result" 184 | } 185 | ], 186 | "source": [ 187 | "y" 188 | ] 189 | }, 190 | { 191 | "cell_type": "code", 192 | "execution_count": 12, 193 | "metadata": {}, 194 | "outputs": [], 195 | "source": [ 196 | "x=5" 197 | ] 198 | }, 199 | { 200 | "cell_type": "code", 201 | "execution_count": 13, 202 | "metadata": {}, 203 | "outputs": [ 204 | { 205 | "data": { 206 | "text/plain": [ 207 | "False" 208 | ] 209 | }, 210 | "execution_count": 13, 211 | "metadata": {}, 212 | "output_type": "execute_result" 213 | } 214 | ], 215 | "source": [ 216 | "x == y" 217 | ] 218 | }, 219 | { 220 | "cell_type": "code", 221 | "execution_count": 14, 222 | "metadata": {}, 223 | "outputs": [ 224 | { 225 | "data": { 226 | "text/plain": [ 227 | "True" 228 | ] 229 | }, 230 | "execution_count": 14, 231 | "metadata": {}, 232 | "output_type": "execute_result" 233 | } 234 | ], 235 | "source": [ 236 | "x != y" 237 | ] 238 | }, 239 | { 240 | "cell_type": "markdown", 241 | "metadata": {}, 242 | "source": [ 243 | "# and or not" 244 | ] 245 | }, 246 | { 247 | "cell_type": "code", 248 | "execution_count": 16, 249 | "metadata": {}, 250 | "outputs": [ 251 | { 252 | "data": { 253 | "text/plain": [ 254 | "True" 255 | ] 256 | }, 257 | "execution_count": 16, 258 | "metadata": {}, 259 | "output_type": "execute_result" 260 | } 261 | ], 262 | "source": [ 263 | "2 > 1 and 3 > 2" 264 | ] 265 | }, 266 | { 267 | "cell_type": "code", 268 | "execution_count": 17, 269 | "metadata": {}, 270 | "outputs": [ 271 | { 272 | "data": { 273 | "text/plain": [ 274 | "False" 275 | ] 276 | }, 277 | "execution_count": 17, 278 | "metadata": {}, 279 | "output_type": "execute_result" 280 | } 281 | ], 282 | "source": [ 283 | "2 < 1 and 3 > 2" 284 | ] 285 | }, 286 | { 287 | "cell_type": "code", 288 | "execution_count": 18, 289 | "metadata": {}, 290 | "outputs": [ 291 | { 292 | "data": { 293 | "text/plain": [ 294 | "True" 295 | ] 296 | }, 297 | "execution_count": 18, 298 | "metadata": {}, 299 | "output_type": "execute_result" 300 | } 301 | ], 302 | "source": [ 303 | "2 < 1 or 3 > 2" 304 | ] 305 | }, 306 | { 307 | "cell_type": "code", 308 | "execution_count": 19, 309 | "metadata": {}, 310 | "outputs": [ 311 | { 312 | "data": { 313 | "text/plain": [ 314 | "False" 315 | ] 316 | }, 317 | "execution_count": 19, 318 | "metadata": {}, 319 | "output_type": "execute_result" 320 | } 321 | ], 322 | "source": [ 323 | "not 10 == 10" 324 | ] 325 | }, 326 | { 327 | "cell_type": "code", 328 | "execution_count": null, 329 | "metadata": {}, 330 | "outputs": [], 331 | "source": [] 332 | } 333 | ], 334 | "metadata": { 335 | "kernelspec": { 336 | "display_name": "Python 3", 337 | "language": "python", 338 | "name": "python3" 339 | }, 340 | "language_info": { 341 | "codemirror_mode": { 342 | "name": "ipython", 343 | "version": 3 344 | }, 345 | "file_extension": ".py", 346 | "mimetype": "text/x-python", 347 | "name": "python", 348 | "nbconvert_exporter": "python", 349 | "pygments_lexer": "ipython3", 350 | "version": "3.6.4" 351 | } 352 | }, 353 | "nbformat": 4, 354 | "nbformat_minor": 2 355 | } 356 | -------------------------------------------------------------------------------- /12-IfStatements.ipynb: -------------------------------------------------------------------------------- 1 | { 2 | "cells": [ 3 | { 4 | "cell_type": "code", 5 | "execution_count": 3, 6 | "metadata": {}, 7 | "outputs": [ 8 | { 9 | "name": "stdout", 10 | "output_type": "stream", 11 | "text": [ 12 | "atil samancioglu\n", 13 | "3 2 1\n" 14 | ] 15 | } 16 | ], 17 | "source": [ 18 | "if 3 > 2:\n", 19 | " print(\"atil samancioglu\")\n", 20 | " print(\"3 2 1\")" 21 | ] 22 | }, 23 | { 24 | "cell_type": "code", 25 | "execution_count": 17, 26 | "metadata": {}, 27 | "outputs": [], 28 | "source": [ 29 | "x = 4" 30 | ] 31 | }, 32 | { 33 | "cell_type": "code", 34 | "execution_count": 18, 35 | "metadata": {}, 36 | "outputs": [], 37 | "source": [ 38 | "y = 4" 39 | ] 40 | }, 41 | { 42 | "cell_type": "code", 43 | "execution_count": 21, 44 | "metadata": {}, 45 | "outputs": [ 46 | { 47 | "name": "stdout", 48 | "output_type": "stream", 49 | "text": [ 50 | "x is y\n" 51 | ] 52 | } 53 | ], 54 | "source": [ 55 | "if x > y:\n", 56 | " print(\"x is greater\")\n", 57 | "elif x == y:\n", 58 | " print(\"x is y\")\n", 59 | "else:\n", 60 | " print(\"y is greater\")" 61 | ] 62 | }, 63 | { 64 | "cell_type": "code", 65 | "execution_count": 27, 66 | "metadata": {}, 67 | "outputs": [ 68 | { 69 | "name": "stdout", 70 | "output_type": "stream", 71 | "text": [ 72 | "superhero: Aquaman\n" 73 | ] 74 | } 75 | ], 76 | "source": [ 77 | "my_superhero = input(\"superhero: \")" 78 | ] 79 | }, 80 | { 81 | "cell_type": "code", 82 | "execution_count": 28, 83 | "metadata": {}, 84 | "outputs": [ 85 | { 86 | "name": "stdout", 87 | "output_type": "stream", 88 | "text": [ 89 | ":(\n" 90 | ] 91 | } 92 | ], 93 | "source": [ 94 | "if my_superhero == \"Batman\":\n", 95 | " print(\"Batmaaaan\")\n", 96 | "elif my_superhero == \"Superman\":\n", 97 | " print(\"Supermaan\")\n", 98 | "elif my_superhero == \"Ironman\":\n", 99 | " print(\"Ironmaaan\")\n", 100 | "elif my_superhero == \"Wonderwoman\":\n", 101 | " print(\"Wonderwomaan\")\n", 102 | "else:\n", 103 | " print(\":(\")" 104 | ] 105 | }, 106 | { 107 | "cell_type": "code", 108 | "execution_count": 29, 109 | "metadata": {}, 110 | "outputs": [], 111 | "source": [ 112 | "a = 10" 113 | ] 114 | }, 115 | { 116 | "cell_type": "code", 117 | "execution_count": 30, 118 | "metadata": {}, 119 | "outputs": [], 120 | "source": [ 121 | "b = 15" 122 | ] 123 | }, 124 | { 125 | "cell_type": "code", 126 | "execution_count": 31, 127 | "metadata": {}, 128 | "outputs": [], 129 | "source": [ 130 | "c = 20" 131 | ] 132 | }, 133 | { 134 | "cell_type": "code", 135 | "execution_count": 34, 136 | "metadata": {}, 137 | "outputs": [ 138 | { 139 | "name": "stdout", 140 | "output_type": "stream", 141 | "text": [ 142 | "superman\n" 143 | ] 144 | } 145 | ], 146 | "source": [ 147 | "if a > b or b < c:\n", 148 | " print(\"superman\")\n", 149 | "elif a < b and b > c:\n", 150 | " print(\"batman\")\n", 151 | "else:\n", 152 | " print(\"aquaman\")" 153 | ] 154 | }, 155 | { 156 | "cell_type": "code", 157 | "execution_count": 36, 158 | "metadata": {}, 159 | "outputs": [], 160 | "source": [ 161 | "isDead = False" 162 | ] 163 | }, 164 | { 165 | "cell_type": "code", 166 | "execution_count": 39, 167 | "metadata": {}, 168 | "outputs": [ 169 | { 170 | "name": "stdout", 171 | "output_type": "stream", 172 | "text": [ 173 | "character is not dead\n" 174 | ] 175 | } 176 | ], 177 | "source": [ 178 | "if isDead == True:\n", 179 | " print(\"character is dead\")\n", 180 | "else:\n", 181 | " print(\"character is not dead\")" 182 | ] 183 | }, 184 | { 185 | "cell_type": "code", 186 | "execution_count": 40, 187 | "metadata": {}, 188 | "outputs": [ 189 | { 190 | "name": "stdout", 191 | "output_type": "stream", 192 | "text": [ 193 | "character is not dead\n" 194 | ] 195 | } 196 | ], 197 | "source": [ 198 | "if isDead:\n", 199 | " print(\"character is dead\")\n", 200 | "else:\n", 201 | " print(\"character is not dead\")" 202 | ] 203 | }, 204 | { 205 | "cell_type": "code", 206 | "execution_count": 41, 207 | "metadata": {}, 208 | "outputs": [ 209 | { 210 | "name": "stdout", 211 | "output_type": "stream", 212 | "text": [ 213 | "character is not dead\n" 214 | ] 215 | } 216 | ], 217 | "source": [ 218 | "if not isDead:\n", 219 | " print(\"character is not dead\")" 220 | ] 221 | }, 222 | { 223 | "cell_type": "code", 224 | "execution_count": 42, 225 | "metadata": {}, 226 | "outputs": [], 227 | "source": [ 228 | "my_string = \"Hello World\"" 229 | ] 230 | }, 231 | { 232 | "cell_type": "code", 233 | "execution_count": 44, 234 | "metadata": {}, 235 | "outputs": [], 236 | "source": [ 237 | "if my_string == \"hello World\":\n", 238 | " print(\"equal\")" 239 | ] 240 | }, 241 | { 242 | "cell_type": "code", 243 | "execution_count": 47, 244 | "metadata": {}, 245 | "outputs": [ 246 | { 247 | "name": "stdout", 248 | "output_type": "stream", 249 | "text": [ 250 | "true\n" 251 | ] 252 | } 253 | ], 254 | "source": [ 255 | "if \"Hello\" in my_string:\n", 256 | " print(\"true\")\n", 257 | "else:\n", 258 | " print(\"false\")" 259 | ] 260 | }, 261 | { 262 | "cell_type": "code", 263 | "execution_count": 48, 264 | "metadata": {}, 265 | "outputs": [], 266 | "source": [ 267 | "my_list = [1,2,3,4,5]" 268 | ] 269 | }, 270 | { 271 | "cell_type": "code", 272 | "execution_count": 49, 273 | "metadata": {}, 274 | "outputs": [ 275 | { 276 | "name": "stdout", 277 | "output_type": "stream", 278 | "text": [ 279 | "true\n" 280 | ] 281 | } 282 | ], 283 | "source": [ 284 | "if 2 in my_list:\n", 285 | " print(\"true\")\n", 286 | "else:\n", 287 | " print(\"false\")" 288 | ] 289 | }, 290 | { 291 | "cell_type": "code", 292 | "execution_count": 50, 293 | "metadata": {}, 294 | "outputs": [], 295 | "source": [ 296 | "my_dictionary = {\"k1\": 100, \"k2\":200, \"k3\":300}" 297 | ] 298 | }, 299 | { 300 | "cell_type": "code", 301 | "execution_count": 55, 302 | "metadata": {}, 303 | "outputs": [ 304 | { 305 | "name": "stdout", 306 | "output_type": "stream", 307 | "text": [ 308 | "true\n" 309 | ] 310 | } 311 | ], 312 | "source": [ 313 | "if 200 in my_dictionary.values():\n", 314 | " print(\"true\")\n", 315 | "else:\n", 316 | " print(\"false\")" 317 | ] 318 | }, 319 | { 320 | "cell_type": "code", 321 | "execution_count": null, 322 | "metadata": {}, 323 | "outputs": [], 324 | "source": [] 325 | } 326 | ], 327 | "metadata": { 328 | "kernelspec": { 329 | "display_name": "Python 3", 330 | "language": "python", 331 | "name": "python3" 332 | }, 333 | "language_info": { 334 | "codemirror_mode": { 335 | "name": "ipython", 336 | "version": 3 337 | }, 338 | "file_extension": ".py", 339 | "mimetype": "text/x-python", 340 | "name": "python", 341 | "nbconvert_exporter": "python", 342 | "pygments_lexer": "ipython3", 343 | "version": "3.6.4" 344 | } 345 | }, 346 | "nbformat": 4, 347 | "nbformat_minor": 2 348 | } 349 | -------------------------------------------------------------------------------- /13-ForLoop.ipynb: -------------------------------------------------------------------------------- 1 | { 2 | "cells": [ 3 | { 4 | "cell_type": "code", 5 | "execution_count": 1, 6 | "metadata": {}, 7 | "outputs": [], 8 | "source": [ 9 | "my_list = [1,2,3,4,5]" 10 | ] 11 | }, 12 | { 13 | "cell_type": "code", 14 | "execution_count": 3, 15 | "metadata": {}, 16 | "outputs": [ 17 | { 18 | "name": "stdout", 19 | "output_type": "stream", 20 | "text": [ 21 | "1\n", 22 | "2\n", 23 | "3\n", 24 | "4\n", 25 | "5\n" 26 | ] 27 | } 28 | ], 29 | "source": [ 30 | "for number in my_list:\n", 31 | " print(number)" 32 | ] 33 | }, 34 | { 35 | "cell_type": "code", 36 | "execution_count": 4, 37 | "metadata": {}, 38 | "outputs": [ 39 | { 40 | "name": "stdout", 41 | "output_type": "stream", 42 | "text": [ 43 | "5\n", 44 | "10\n", 45 | "15\n", 46 | "20\n", 47 | "25\n" 48 | ] 49 | } 50 | ], 51 | "source": [ 52 | "for item in my_list:\n", 53 | " new_number = item * 5\n", 54 | " print(new_number)" 55 | ] 56 | }, 57 | { 58 | "cell_type": "code", 59 | "execution_count": 8, 60 | "metadata": {}, 61 | "outputs": [ 62 | { 63 | "name": "stdout", 64 | "output_type": "stream", 65 | "text": [ 66 | "2\n", 67 | "4\n" 68 | ] 69 | } 70 | ], 71 | "source": [ 72 | "for number in my_list:\n", 73 | " if number % 2 == 0:\n", 74 | " print(number)" 75 | ] 76 | }, 77 | { 78 | "cell_type": "code", 79 | "execution_count": 9, 80 | "metadata": {}, 81 | "outputs": [ 82 | { 83 | "name": "stdout", 84 | "output_type": "stream", 85 | "text": [ 86 | "true\n" 87 | ] 88 | } 89 | ], 90 | "source": [ 91 | "if 2 in my_list:\n", 92 | " print(\"true\")" 93 | ] 94 | }, 95 | { 96 | "cell_type": "code", 97 | "execution_count": 10, 98 | "metadata": {}, 99 | "outputs": [ 100 | { 101 | "name": "stdout", 102 | "output_type": "stream", 103 | "text": [ 104 | "true\n" 105 | ] 106 | } 107 | ], 108 | "source": [ 109 | "for num in my_list:\n", 110 | " if num == 2:\n", 111 | " print(\"true\")" 112 | ] 113 | }, 114 | { 115 | "cell_type": "code", 116 | "execution_count": 11, 117 | "metadata": {}, 118 | "outputs": [], 119 | "source": [ 120 | "my_string = \"James Hetfield\"" 121 | ] 122 | }, 123 | { 124 | "cell_type": "code", 125 | "execution_count": 13, 126 | "metadata": {}, 127 | "outputs": [ 128 | { 129 | "name": "stdout", 130 | "output_type": "stream", 131 | "text": [ 132 | "J\n", 133 | "a\n", 134 | "m\n", 135 | "e\n", 136 | "s\n", 137 | " \n", 138 | "H\n", 139 | "e\n", 140 | "t\n", 141 | "f\n", 142 | "i\n", 143 | "e\n", 144 | "l\n", 145 | "d\n" 146 | ] 147 | } 148 | ], 149 | "source": [ 150 | "for letter in my_string:\n", 151 | " print(letter)" 152 | ] 153 | }, 154 | { 155 | "cell_type": "code", 156 | "execution_count": 14, 157 | "metadata": {}, 158 | "outputs": [], 159 | "source": [ 160 | "my_tuple = (1,2,3)" 161 | ] 162 | }, 163 | { 164 | "cell_type": "code", 165 | "execution_count": 17, 166 | "metadata": {}, 167 | "outputs": [ 168 | { 169 | "name": "stdout", 170 | "output_type": "stream", 171 | "text": [ 172 | "-5\n", 173 | "0\n", 174 | "5\n" 175 | ] 176 | } 177 | ], 178 | "source": [ 179 | "for item in my_tuple:\n", 180 | " print(item * 5 - 10)" 181 | ] 182 | }, 183 | { 184 | "cell_type": "code", 185 | "execution_count": 18, 186 | "metadata": {}, 187 | "outputs": [], 188 | "source": [ 189 | "my_new_list = [(\"a\",\"b\"),(\"c\",\"d\"),(\"e\",\"f\"),(\"g\",\"h\")]" 190 | ] 191 | }, 192 | { 193 | "cell_type": "code", 194 | "execution_count": 19, 195 | "metadata": {}, 196 | "outputs": [ 197 | { 198 | "name": "stdout", 199 | "output_type": "stream", 200 | "text": [ 201 | "('a', 'b')\n", 202 | "('c', 'd')\n", 203 | "('e', 'f')\n", 204 | "('g', 'h')\n" 205 | ] 206 | } 207 | ], 208 | "source": [ 209 | "for element in my_new_list:\n", 210 | " print(element)" 211 | ] 212 | }, 213 | { 214 | "cell_type": "code", 215 | "execution_count": 22, 216 | "metadata": {}, 217 | "outputs": [ 218 | { 219 | "name": "stdout", 220 | "output_type": "stream", 221 | "text": [ 222 | "a\n", 223 | "b\n", 224 | "c\n", 225 | "d\n", 226 | "e\n", 227 | "f\n", 228 | "g\n", 229 | "h\n" 230 | ] 231 | } 232 | ], 233 | "source": [ 234 | "for (x,y) in my_new_list:\n", 235 | " print(x)\n", 236 | " print(y)" 237 | ] 238 | }, 239 | { 240 | "cell_type": "code", 241 | "execution_count": 23, 242 | "metadata": {}, 243 | "outputs": [], 244 | "source": [ 245 | "my_tuple_list = [(0,1,2),(3,4,5),(9,10,11)]" 246 | ] 247 | }, 248 | { 249 | "cell_type": "code", 250 | "execution_count": 32, 251 | "metadata": {}, 252 | "outputs": [ 253 | { 254 | "name": "stdout", 255 | "output_type": "stream", 256 | "text": [ 257 | "2\n", 258 | "5\n", 259 | "11\n" 260 | ] 261 | } 262 | ], 263 | "source": [ 264 | "for (x,y,z) in my_tuple_list:\n", 265 | " print(z)" 266 | ] 267 | }, 268 | { 269 | "cell_type": "code", 270 | "execution_count": 33, 271 | "metadata": {}, 272 | "outputs": [], 273 | "source": [ 274 | "my_dictionary = {\"key1\": 100, \"key2\" : 200, \"key3\" : 300}" 275 | ] 276 | }, 277 | { 278 | "cell_type": "code", 279 | "execution_count": 34, 280 | "metadata": {}, 281 | "outputs": [ 282 | { 283 | "name": "stdout", 284 | "output_type": "stream", 285 | "text": [ 286 | "key1\n", 287 | "key2\n", 288 | "key3\n" 289 | ] 290 | } 291 | ], 292 | "source": [ 293 | "for (key,value) in my_dictionary.items():\n", 294 | " print(key)" 295 | ] 296 | }, 297 | { 298 | "cell_type": "code", 299 | "execution_count": null, 300 | "metadata": {}, 301 | "outputs": [], 302 | "source": [] 303 | } 304 | ], 305 | "metadata": { 306 | "kernelspec": { 307 | "display_name": "Python 3", 308 | "language": "python", 309 | "name": "python3" 310 | }, 311 | "language_info": { 312 | "codemirror_mode": { 313 | "name": "ipython", 314 | "version": 3 315 | }, 316 | "file_extension": ".py", 317 | "mimetype": "text/x-python", 318 | "name": "python", 319 | "nbconvert_exporter": "python", 320 | "pygments_lexer": "ipython3", 321 | "version": "3.6.4" 322 | } 323 | }, 324 | "nbformat": 4, 325 | "nbformat_minor": 2 326 | } 327 | -------------------------------------------------------------------------------- /14-ContinueBreakPass.ipynb: -------------------------------------------------------------------------------- 1 | { 2 | "cells": [ 3 | { 4 | "cell_type": "code", 5 | "execution_count": 1, 6 | "metadata": {}, 7 | "outputs": [], 8 | "source": [ 9 | "my_list = [10,20,30,40,50,60]" 10 | ] 11 | }, 12 | { 13 | "cell_type": "code", 14 | "execution_count": 7, 15 | "metadata": {}, 16 | "outputs": [ 17 | { 18 | "name": "stdout", 19 | "output_type": "stream", 20 | "text": [ 21 | "50\n", 22 | "100\n", 23 | "150\n", 24 | "200\n", 25 | "250\n", 26 | "300\n" 27 | ] 28 | } 29 | ], 30 | "source": [ 31 | "for number in my_list:\n", 32 | " print(number * 5)" 33 | ] 34 | }, 35 | { 36 | "cell_type": "code", 37 | "execution_count": 10, 38 | "metadata": {}, 39 | "outputs": [ 40 | { 41 | "name": "stdout", 42 | "output_type": "stream", 43 | "text": [ 44 | "50\n", 45 | "100\n" 46 | ] 47 | } 48 | ], 49 | "source": [ 50 | "for num in my_list:\n", 51 | " if num == 30:\n", 52 | " break\n", 53 | " print(num * 5)" 54 | ] 55 | }, 56 | { 57 | "cell_type": "code", 58 | "execution_count": 11, 59 | "metadata": {}, 60 | "outputs": [ 61 | { 62 | "name": "stdout", 63 | "output_type": "stream", 64 | "text": [ 65 | "50\n", 66 | "100\n", 67 | "200\n", 68 | "250\n", 69 | "300\n" 70 | ] 71 | } 72 | ], 73 | "source": [ 74 | "for item in my_list:\n", 75 | " if item == 30:\n", 76 | " continue\n", 77 | " print( item * 5)" 78 | ] 79 | }, 80 | { 81 | "cell_type": "code", 82 | "execution_count": 13, 83 | "metadata": {}, 84 | "outputs": [], 85 | "source": [ 86 | "for no in my_list:\n", 87 | " pass" 88 | ] 89 | }, 90 | { 91 | "cell_type": "code", 92 | "execution_count": null, 93 | "metadata": {}, 94 | "outputs": [], 95 | "source": [] 96 | } 97 | ], 98 | "metadata": { 99 | "kernelspec": { 100 | "display_name": "Python 3", 101 | "language": "python", 102 | "name": "python3" 103 | }, 104 | "language_info": { 105 | "codemirror_mode": { 106 | "name": "ipython", 107 | "version": 3 108 | }, 109 | "file_extension": ".py", 110 | "mimetype": "text/x-python", 111 | "name": "python", 112 | "nbconvert_exporter": "python", 113 | "pygments_lexer": "ipython3", 114 | "version": "3.6.4" 115 | } 116 | }, 117 | "nbformat": 4, 118 | "nbformat_minor": 2 119 | } 120 | -------------------------------------------------------------------------------- /15-WhileLoop.ipynb: -------------------------------------------------------------------------------- 1 | { 2 | "cells": [ 3 | { 4 | "cell_type": "code", 5 | "execution_count": 1, 6 | "metadata": {}, 7 | "outputs": [], 8 | "source": [ 9 | "a = 0" 10 | ] 11 | }, 12 | { 13 | "cell_type": "code", 14 | "execution_count": 2, 15 | "metadata": {}, 16 | "outputs": [ 17 | { 18 | "name": "stdout", 19 | "output_type": "stream", 20 | "text": [ 21 | "hello\n", 22 | "hello\n", 23 | "hello\n", 24 | "hello\n", 25 | "hello\n", 26 | "hello\n" 27 | ] 28 | } 29 | ], 30 | "source": [ 31 | "while a <= 5:\n", 32 | " print(\"hello\")\n", 33 | " a = a + 1" 34 | ] 35 | }, 36 | { 37 | "cell_type": "code", 38 | "execution_count": 3, 39 | "metadata": {}, 40 | "outputs": [], 41 | "source": [ 42 | "my_list = [1,2,3,4,5]" 43 | ] 44 | }, 45 | { 46 | "cell_type": "code", 47 | "execution_count": 4, 48 | "metadata": {}, 49 | "outputs": [ 50 | { 51 | "data": { 52 | "text/plain": [ 53 | "5" 54 | ] 55 | }, 56 | "execution_count": 4, 57 | "metadata": {}, 58 | "output_type": "execute_result" 59 | } 60 | ], 61 | "source": [ 62 | "my_list.pop()" 63 | ] 64 | }, 65 | { 66 | "cell_type": "code", 67 | "execution_count": 5, 68 | "metadata": {}, 69 | "outputs": [ 70 | { 71 | "data": { 72 | "text/plain": [ 73 | "[1, 2, 3, 4]" 74 | ] 75 | }, 76 | "execution_count": 5, 77 | "metadata": {}, 78 | "output_type": "execute_result" 79 | } 80 | ], 81 | "source": [ 82 | "my_list" 83 | ] 84 | }, 85 | { 86 | "cell_type": "code", 87 | "execution_count": 6, 88 | "metadata": {}, 89 | "outputs": [], 90 | "source": [ 91 | "my_list.append(5)" 92 | ] 93 | }, 94 | { 95 | "cell_type": "code", 96 | "execution_count": 7, 97 | "metadata": {}, 98 | "outputs": [ 99 | { 100 | "data": { 101 | "text/plain": [ 102 | "[1, 2, 3, 4, 5]" 103 | ] 104 | }, 105 | "execution_count": 7, 106 | "metadata": {}, 107 | "output_type": "execute_result" 108 | } 109 | ], 110 | "source": [ 111 | "my_list" 112 | ] 113 | }, 114 | { 115 | "cell_type": "code", 116 | "execution_count": 8, 117 | "metadata": {}, 118 | "outputs": [ 119 | { 120 | "name": "stdout", 121 | "output_type": "stream", 122 | "text": [ 123 | "3 in my list\n", 124 | "3 in my list\n", 125 | "3 in my list\n" 126 | ] 127 | } 128 | ], 129 | "source": [ 130 | "while 3 in my_list:\n", 131 | " print(\"3 in my list\")\n", 132 | " my_list.pop()" 133 | ] 134 | }, 135 | { 136 | "cell_type": "code", 137 | "execution_count": 9, 138 | "metadata": {}, 139 | "outputs": [], 140 | "source": [ 141 | "number = 0" 142 | ] 143 | }, 144 | { 145 | "cell_type": "code", 146 | "execution_count": 10, 147 | "metadata": {}, 148 | "outputs": [ 149 | { 150 | "name": "stdout", 151 | "output_type": "stream", 152 | "text": [ 153 | "0\n", 154 | "1\n", 155 | "2\n", 156 | "3\n", 157 | "4\n" 158 | ] 159 | } 160 | ], 161 | "source": [ 162 | "while number < 5:\n", 163 | " #if number == 5:\n", 164 | " # break\n", 165 | " print(number)\n", 166 | " number += 1" 167 | ] 168 | }, 169 | { 170 | "cell_type": "code", 171 | "execution_count": 19, 172 | "metadata": {}, 173 | "outputs": [], 174 | "source": [ 175 | "p = 0" 176 | ] 177 | }, 178 | { 179 | "cell_type": "code", 180 | "execution_count": 20, 181 | "metadata": {}, 182 | "outputs": [ 183 | { 184 | "name": "stdout", 185 | "output_type": "stream", 186 | "text": [ 187 | "value p p p: 0\n", 188 | "value p p p: 1\n", 189 | "value p p p: 2\n", 190 | "value p p p: 3\n", 191 | "value p p p: 4\n", 192 | "value p p p: 5\n", 193 | "value p p p: 6\n", 194 | "value p p p: 7\n", 195 | "value p p p: 8\n", 196 | "value p p p: 9\n", 197 | "value p p p: 10\n", 198 | "value p p p: 11\n", 199 | "value p p p: 12\n", 200 | "value p p p: 13\n", 201 | "value p p p: 14\n", 202 | "value p p p: 15\n", 203 | "value p p p: 16\n", 204 | "value p p p: 17\n", 205 | "value p p p: 18\n", 206 | "value p p p: 19\n" 207 | ] 208 | } 209 | ], 210 | "source": [ 211 | "while p < 20:\n", 212 | " #print(\"value p: \" + str(p))\n", 213 | " print(f\"value p p p: {p}\")\n", 214 | " p += 1" 215 | ] 216 | }, 217 | { 218 | "cell_type": "code", 219 | "execution_count": null, 220 | "metadata": {}, 221 | "outputs": [], 222 | "source": [] 223 | } 224 | ], 225 | "metadata": { 226 | "kernelspec": { 227 | "display_name": "Python 3", 228 | "language": "python", 229 | "name": "python3" 230 | }, 231 | "language_info": { 232 | "codemirror_mode": { 233 | "name": "ipython", 234 | "version": 3 235 | }, 236 | "file_extension": ".py", 237 | "mimetype": "text/x-python", 238 | "name": "python", 239 | "nbconvert_exporter": "python", 240 | "pygments_lexer": "ipython3", 241 | "version": "3.6.4" 242 | } 243 | }, 244 | "nbformat": 4, 245 | "nbformat_minor": 2 246 | } 247 | -------------------------------------------------------------------------------- /16-UsefulMethods.ipynb: -------------------------------------------------------------------------------- 1 | { 2 | "cells": [ 3 | { 4 | "cell_type": "code", 5 | "execution_count": 1, 6 | "metadata": {}, 7 | "outputs": [], 8 | "source": [ 9 | "my_list = [1,2,3,4,5,6,7]" 10 | ] 11 | }, 12 | { 13 | "cell_type": "code", 14 | "execution_count": 2, 15 | "metadata": {}, 16 | "outputs": [ 17 | { 18 | "name": "stdout", 19 | "output_type": "stream", 20 | "text": [ 21 | "1\n", 22 | "2\n", 23 | "3\n", 24 | "4\n", 25 | "5\n", 26 | "6\n", 27 | "7\n" 28 | ] 29 | } 30 | ], 31 | "source": [ 32 | "for number in my_list:\n", 33 | " print(number)" 34 | ] 35 | }, 36 | { 37 | "cell_type": "markdown", 38 | "metadata": {}, 39 | "source": [ 40 | "## range" 41 | ] 42 | }, 43 | { 44 | "cell_type": "code", 45 | "execution_count": 3, 46 | "metadata": {}, 47 | "outputs": [ 48 | { 49 | "data": { 50 | "text/plain": [ 51 | "range(0, 20)" 52 | ] 53 | }, 54 | "execution_count": 3, 55 | "metadata": {}, 56 | "output_type": "execute_result" 57 | } 58 | ], 59 | "source": [ 60 | "range(20)" 61 | ] 62 | }, 63 | { 64 | "cell_type": "code", 65 | "execution_count": 4, 66 | "metadata": {}, 67 | "outputs": [ 68 | { 69 | "data": { 70 | "text/plain": [ 71 | "[0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19]" 72 | ] 73 | }, 74 | "execution_count": 4, 75 | "metadata": {}, 76 | "output_type": "execute_result" 77 | } 78 | ], 79 | "source": [ 80 | "list(range(20))" 81 | ] 82 | }, 83 | { 84 | "cell_type": "code", 85 | "execution_count": 5, 86 | "metadata": {}, 87 | "outputs": [ 88 | { 89 | "name": "stdout", 90 | "output_type": "stream", 91 | "text": [ 92 | "0\n", 93 | "5\n", 94 | "10\n", 95 | "15\n", 96 | "20\n", 97 | "25\n", 98 | "30\n", 99 | "35\n", 100 | "40\n", 101 | "45\n", 102 | "50\n", 103 | "55\n", 104 | "60\n", 105 | "65\n", 106 | "70\n", 107 | "75\n", 108 | "80\n", 109 | "85\n", 110 | "90\n", 111 | "95\n" 112 | ] 113 | } 114 | ], 115 | "source": [ 116 | "for number in list(range(20)):\n", 117 | " print(number * 5 )" 118 | ] 119 | }, 120 | { 121 | "cell_type": "code", 122 | "execution_count": 9, 123 | "metadata": {}, 124 | "outputs": [ 125 | { 126 | "name": "stdout", 127 | "output_type": "stream", 128 | "text": [ 129 | "5\n", 130 | "9\n", 131 | "13\n", 132 | "17\n" 133 | ] 134 | } 135 | ], 136 | "source": [ 137 | "for num in list(range(5,21,4)):\n", 138 | " print(num)" 139 | ] 140 | }, 141 | { 142 | "cell_type": "markdown", 143 | "metadata": {}, 144 | "source": [ 145 | "## enumerate" 146 | ] 147 | }, 148 | { 149 | "cell_type": "code", 150 | "execution_count": 15, 151 | "metadata": {}, 152 | "outputs": [ 153 | { 154 | "name": "stdout", 155 | "output_type": "stream", 156 | "text": [ 157 | "no: 5 ix: 0\n", 158 | "no: 6 ix: 1\n", 159 | "no: 7 ix: 2\n", 160 | "no: 8 ix: 3\n", 161 | "no: 9 ix: 4\n", 162 | "no: 10 ix: 5\n", 163 | "no: 11 ix: 6\n", 164 | "no: 12 ix: 7\n", 165 | "no: 13 ix: 8\n", 166 | "no: 14 ix: 9\n" 167 | ] 168 | } 169 | ], 170 | "source": [ 171 | "index = 0\n", 172 | "for number in list(range(5,15)):\n", 173 | " print(f\"no: {number} ix: {index}\")\n", 174 | " index += 1" 175 | ] 176 | }, 177 | { 178 | "cell_type": "code", 179 | "execution_count": 16, 180 | "metadata": {}, 181 | "outputs": [ 182 | { 183 | "name": "stdout", 184 | "output_type": "stream", 185 | "text": [ 186 | "(0, 5)\n", 187 | "(1, 6)\n", 188 | "(2, 7)\n", 189 | "(3, 8)\n", 190 | "(4, 9)\n", 191 | "(5, 10)\n", 192 | "(6, 11)\n", 193 | "(7, 12)\n", 194 | "(8, 13)\n", 195 | "(9, 14)\n" 196 | ] 197 | } 198 | ], 199 | "source": [ 200 | "for element in enumerate(list(range(5,15))):\n", 201 | " print(element)" 202 | ] 203 | }, 204 | { 205 | "cell_type": "code", 206 | "execution_count": 17, 207 | "metadata": {}, 208 | "outputs": [ 209 | { 210 | "name": "stdout", 211 | "output_type": "stream", 212 | "text": [ 213 | "0\n", 214 | "5\n", 215 | "1\n", 216 | "6\n", 217 | "2\n", 218 | "7\n", 219 | "3\n", 220 | "8\n", 221 | "4\n", 222 | "9\n", 223 | "5\n", 224 | "10\n", 225 | "6\n", 226 | "11\n", 227 | "7\n", 228 | "12\n", 229 | "8\n", 230 | "13\n", 231 | "9\n", 232 | "14\n" 233 | ] 234 | } 235 | ], 236 | "source": [ 237 | "for (index,number) in enumerate(list(range(5,15))):\n", 238 | " print(index)\n", 239 | " print(number)" 240 | ] 241 | }, 242 | { 243 | "cell_type": "markdown", 244 | "metadata": {}, 245 | "source": [ 246 | "## random" 247 | ] 248 | }, 249 | { 250 | "cell_type": "code", 251 | "execution_count": 18, 252 | "metadata": {}, 253 | "outputs": [], 254 | "source": [ 255 | "from random import randint" 256 | ] 257 | }, 258 | { 259 | "cell_type": "code", 260 | "execution_count": 19, 261 | "metadata": {}, 262 | "outputs": [ 263 | { 264 | "data": { 265 | "text/plain": [ 266 | "687" 267 | ] 268 | }, 269 | "execution_count": 19, 270 | "metadata": {}, 271 | "output_type": "execute_result" 272 | } 273 | ], 274 | "source": [ 275 | "randint(0,1000)" 276 | ] 277 | }, 278 | { 279 | "cell_type": "code", 280 | "execution_count": 20, 281 | "metadata": {}, 282 | "outputs": [ 283 | { 284 | "data": { 285 | "text/plain": [ 286 | "746" 287 | ] 288 | }, 289 | "execution_count": 20, 290 | "metadata": {}, 291 | "output_type": "execute_result" 292 | } 293 | ], 294 | "source": [ 295 | "randint(0,1000)" 296 | ] 297 | }, 298 | { 299 | "cell_type": "code", 300 | "execution_count": 21, 301 | "metadata": {}, 302 | "outputs": [], 303 | "source": [ 304 | "my_list_2 = list(range(0,10))" 305 | ] 306 | }, 307 | { 308 | "cell_type": "code", 309 | "execution_count": 22, 310 | "metadata": {}, 311 | "outputs": [ 312 | { 313 | "data": { 314 | "text/plain": [ 315 | "[0, 1, 2, 3, 4, 5, 6, 7, 8, 9]" 316 | ] 317 | }, 318 | "execution_count": 22, 319 | "metadata": {}, 320 | "output_type": "execute_result" 321 | } 322 | ], 323 | "source": [ 324 | "my_list_2" 325 | ] 326 | }, 327 | { 328 | "cell_type": "code", 329 | "execution_count": 23, 330 | "metadata": {}, 331 | "outputs": [], 332 | "source": [ 333 | "from random import shuffle" 334 | ] 335 | }, 336 | { 337 | "cell_type": "code", 338 | "execution_count": 24, 339 | "metadata": {}, 340 | "outputs": [], 341 | "source": [ 342 | "shuffle(my_list_2)" 343 | ] 344 | }, 345 | { 346 | "cell_type": "code", 347 | "execution_count": 25, 348 | "metadata": {}, 349 | "outputs": [ 350 | { 351 | "data": { 352 | "text/plain": [ 353 | "[0, 3, 7, 9, 2, 6, 4, 8, 1, 5]" 354 | ] 355 | }, 356 | "execution_count": 25, 357 | "metadata": {}, 358 | "output_type": "execute_result" 359 | } 360 | ], 361 | "source": [ 362 | "my_list_2" 363 | ] 364 | }, 365 | { 366 | "cell_type": "markdown", 367 | "metadata": {}, 368 | "source": [ 369 | "## zip" 370 | ] 371 | }, 372 | { 373 | "cell_type": "code", 374 | "execution_count": 26, 375 | "metadata": {}, 376 | "outputs": [], 377 | "source": [ 378 | "sport_list = [\"run\",\"swim\",\"basketball\"]" 379 | ] 380 | }, 381 | { 382 | "cell_type": "code", 383 | "execution_count": 27, 384 | "metadata": {}, 385 | "outputs": [], 386 | "source": [ 387 | "calories_list = [100,200,300]" 388 | ] 389 | }, 390 | { 391 | "cell_type": "code", 392 | "execution_count": 28, 393 | "metadata": {}, 394 | "outputs": [], 395 | "source": [ 396 | "day_list = [\"monday\",\"tuesday\",\"wednesday\"]" 397 | ] 398 | }, 399 | { 400 | "cell_type": "code", 401 | "execution_count": 32, 402 | "metadata": {}, 403 | "outputs": [], 404 | "source": [ 405 | "new_list = list(zip(sport_list,calories_list,day_list))" 406 | ] 407 | }, 408 | { 409 | "cell_type": "code", 410 | "execution_count": 33, 411 | "metadata": {}, 412 | "outputs": [ 413 | { 414 | "data": { 415 | "text/plain": [ 416 | "[('run', 100, 'monday'),\n", 417 | " ('swim', 200, 'tuesday'),\n", 418 | " ('basketball', 300, 'wednesday')]" 419 | ] 420 | }, 421 | "execution_count": 33, 422 | "metadata": {}, 423 | "output_type": "execute_result" 424 | } 425 | ], 426 | "source": [ 427 | "new_list" 428 | ] 429 | }, 430 | { 431 | "cell_type": "code", 432 | "execution_count": 34, 433 | "metadata": {}, 434 | "outputs": [ 435 | { 436 | "name": "stdout", 437 | "output_type": "stream", 438 | "text": [ 439 | "('run', 100, 'monday')\n", 440 | "('swim', 200, 'tuesday')\n", 441 | "('basketball', 300, 'wednesday')\n" 442 | ] 443 | } 444 | ], 445 | "source": [ 446 | "for element in new_list:\n", 447 | " print(element)" 448 | ] 449 | }, 450 | { 451 | "cell_type": "markdown", 452 | "metadata": {}, 453 | "source": [ 454 | "## list advanced" 455 | ] 456 | }, 457 | { 458 | "cell_type": "code", 459 | "execution_count": 38, 460 | "metadata": {}, 461 | "outputs": [], 462 | "source": [ 463 | "new_list = []\n", 464 | "my_string = \"metallica\"\n", 465 | "\n", 466 | "for element in my_string:\n", 467 | " new_list.append(element)" 468 | ] 469 | }, 470 | { 471 | "cell_type": "code", 472 | "execution_count": 39, 473 | "metadata": {}, 474 | "outputs": [ 475 | { 476 | "data": { 477 | "text/plain": [ 478 | "['m', 'e', 't', 'a', 'l', 'l', 'i', 'c', 'a']" 479 | ] 480 | }, 481 | "execution_count": 39, 482 | "metadata": {}, 483 | "output_type": "execute_result" 484 | } 485 | ], 486 | "source": [ 487 | "new_list" 488 | ] 489 | }, 490 | { 491 | "cell_type": "code", 492 | "execution_count": 40, 493 | "metadata": {}, 494 | "outputs": [], 495 | "source": [ 496 | "new_list = [element for element in my_string]" 497 | ] 498 | }, 499 | { 500 | "cell_type": "code", 501 | "execution_count": 41, 502 | "metadata": {}, 503 | "outputs": [ 504 | { 505 | "data": { 506 | "text/plain": [ 507 | "['m', 'e', 't', 'a', 'l', 'l', 'i', 'c', 'a']" 508 | ] 509 | }, 510 | "execution_count": 41, 511 | "metadata": {}, 512 | "output_type": "execute_result" 513 | } 514 | ], 515 | "source": [ 516 | "new_list" 517 | ] 518 | }, 519 | { 520 | "cell_type": "code", 521 | "execution_count": 47, 522 | "metadata": {}, 523 | "outputs": [], 524 | "source": [ 525 | "new_list_2 = [number**5 for number in list(range(0,10))]" 526 | ] 527 | }, 528 | { 529 | "cell_type": "code", 530 | "execution_count": 48, 531 | "metadata": {}, 532 | "outputs": [ 533 | { 534 | "data": { 535 | "text/plain": [ 536 | "[0, 1, 32, 243, 1024, 3125, 7776, 16807, 32768, 59049]" 537 | ] 538 | }, 539 | "execution_count": 48, 540 | "metadata": {}, 541 | "output_type": "execute_result" 542 | } 543 | ], 544 | "source": [ 545 | "new_list_2" 546 | ] 547 | }, 548 | { 549 | "cell_type": "code", 550 | "execution_count": null, 551 | "metadata": {}, 552 | "outputs": [], 553 | "source": [] 554 | } 555 | ], 556 | "metadata": { 557 | "kernelspec": { 558 | "display_name": "Python 3", 559 | "language": "python", 560 | "name": "python3" 561 | }, 562 | "language_info": { 563 | "codemirror_mode": { 564 | "name": "ipython", 565 | "version": 3 566 | }, 567 | "file_extension": ".py", 568 | "mimetype": "text/x-python", 569 | "name": "python", 570 | "nbconvert_exporter": "python", 571 | "pygments_lexer": "ipython3", 572 | "version": "3.6.4" 573 | } 574 | }, 575 | "nbformat": 4, 576 | "nbformat_minor": 2 577 | } 578 | -------------------------------------------------------------------------------- /17-MethodsAndFunctions.ipynb: -------------------------------------------------------------------------------- 1 | { 2 | "cells": [ 3 | { 4 | "cell_type": "code", 5 | "execution_count": 2, 6 | "metadata": {}, 7 | "outputs": [], 8 | "source": [ 9 | "my_string = \"Atil\"" 10 | ] 11 | }, 12 | { 13 | "cell_type": "code", 14 | "execution_count": 3, 15 | "metadata": {}, 16 | "outputs": [], 17 | "source": [ 18 | "my_string_upper = my_string.upper()" 19 | ] 20 | }, 21 | { 22 | "cell_type": "code", 23 | "execution_count": 4, 24 | "metadata": {}, 25 | "outputs": [ 26 | { 27 | "data": { 28 | "text/plain": [ 29 | "'Atil'" 30 | ] 31 | }, 32 | "execution_count": 4, 33 | "metadata": {}, 34 | "output_type": "execute_result" 35 | } 36 | ], 37 | "source": [ 38 | "my_string" 39 | ] 40 | }, 41 | { 42 | "cell_type": "code", 43 | "execution_count": 5, 44 | "metadata": {}, 45 | "outputs": [ 46 | { 47 | "data": { 48 | "text/plain": [ 49 | "'ATIL'" 50 | ] 51 | }, 52 | "execution_count": 5, 53 | "metadata": {}, 54 | "output_type": "execute_result" 55 | } 56 | ], 57 | "source": [ 58 | "my_string_upper" 59 | ] 60 | }, 61 | { 62 | "cell_type": "code", 63 | "execution_count": 6, 64 | "metadata": {}, 65 | "outputs": [ 66 | { 67 | "name": "stdout", 68 | "output_type": "stream", 69 | "text": [ 70 | "Help on built-in function split:\n", 71 | "\n", 72 | "split(...) method of builtins.str instance\n", 73 | " S.split(sep=None, maxsplit=-1) -> list of strings\n", 74 | " \n", 75 | " Return a list of the words in S, using sep as the\n", 76 | " delimiter string. If maxsplit is given, at most maxsplit\n", 77 | " splits are done. If sep is not specified or is None, any\n", 78 | " whitespace string is a separator and empty strings are\n", 79 | " removed from the result.\n", 80 | "\n" 81 | ] 82 | } 83 | ], 84 | "source": [ 85 | "help(my_string.split)" 86 | ] 87 | }, 88 | { 89 | "cell_type": "code", 90 | "execution_count": 7, 91 | "metadata": {}, 92 | "outputs": [], 93 | "source": [ 94 | "def hello_world():\n", 95 | " print(\"hello\")\n", 96 | " print(\"world\") " 97 | ] 98 | }, 99 | { 100 | "cell_type": "code", 101 | "execution_count": 8, 102 | "metadata": {}, 103 | "outputs": [ 104 | { 105 | "data": { 106 | "text/plain": [ 107 | "" 108 | ] 109 | }, 110 | "execution_count": 8, 111 | "metadata": {}, 112 | "output_type": "execute_result" 113 | } 114 | ], 115 | "source": [ 116 | "hello_world" 117 | ] 118 | }, 119 | { 120 | "cell_type": "code", 121 | "execution_count": 9, 122 | "metadata": {}, 123 | "outputs": [ 124 | { 125 | "name": "stdout", 126 | "output_type": "stream", 127 | "text": [ 128 | "hello\n", 129 | "world\n" 130 | ] 131 | } 132 | ], 133 | "source": [ 134 | "hello_world()" 135 | ] 136 | }, 137 | { 138 | "cell_type": "markdown", 139 | "metadata": {}, 140 | "source": [ 141 | "## input & return" 142 | ] 143 | }, 144 | { 145 | "cell_type": "code", 146 | "execution_count": 10, 147 | "metadata": {}, 148 | "outputs": [], 149 | "source": [ 150 | "def hello_programming(name):\n", 151 | " print(\"hello\")\n", 152 | " print(name)" 153 | ] 154 | }, 155 | { 156 | "cell_type": "code", 157 | "execution_count": 11, 158 | "metadata": {}, 159 | "outputs": [ 160 | { 161 | "name": "stdout", 162 | "output_type": "stream", 163 | "text": [ 164 | "hello\n", 165 | "Python\n" 166 | ] 167 | } 168 | ], 169 | "source": [ 170 | "hello_programming(\"Python\")" 171 | ] 172 | }, 173 | { 174 | "cell_type": "code", 175 | "execution_count": 12, 176 | "metadata": {}, 177 | "outputs": [ 178 | { 179 | "name": "stdout", 180 | "output_type": "stream", 181 | "text": [ 182 | "hello\n", 183 | "Java\n" 184 | ] 185 | } 186 | ], 187 | "source": [ 188 | "hello_programming(\"Java\")" 189 | ] 190 | }, 191 | { 192 | "cell_type": "code", 193 | "execution_count": 13, 194 | "metadata": {}, 195 | "outputs": [], 196 | "source": [ 197 | "def hello_program(name=\"python\"):\n", 198 | " print(\"hello\")\n", 199 | " print(name)" 200 | ] 201 | }, 202 | { 203 | "cell_type": "code", 204 | "execution_count": 14, 205 | "metadata": {}, 206 | "outputs": [ 207 | { 208 | "name": "stdout", 209 | "output_type": "stream", 210 | "text": [ 211 | "hello\n", 212 | "python\n" 213 | ] 214 | } 215 | ], 216 | "source": [ 217 | "hello_program()" 218 | ] 219 | }, 220 | { 221 | "cell_type": "code", 222 | "execution_count": 15, 223 | "metadata": {}, 224 | "outputs": [ 225 | { 226 | "name": "stdout", 227 | "output_type": "stream", 228 | "text": [ 229 | "hello\n", 230 | "java\n" 231 | ] 232 | } 233 | ], 234 | "source": [ 235 | "hello_program(\"java\")" 236 | ] 237 | }, 238 | { 239 | "cell_type": "code", 240 | "execution_count": 16, 241 | "metadata": {}, 242 | "outputs": [], 243 | "source": [ 244 | "def summ(number1,number2):\n", 245 | " number3 = number1 + number2\n", 246 | " print(number3)" 247 | ] 248 | }, 249 | { 250 | "cell_type": "code", 251 | "execution_count": 17, 252 | "metadata": {}, 253 | "outputs": [ 254 | { 255 | "name": "stdout", 256 | "output_type": "stream", 257 | "text": [ 258 | "13\n" 259 | ] 260 | } 261 | ], 262 | "source": [ 263 | "summ(5,8)" 264 | ] 265 | }, 266 | { 267 | "cell_type": "code", 268 | "execution_count": 18, 269 | "metadata": {}, 270 | "outputs": [ 271 | { 272 | "name": "stdout", 273 | "output_type": "stream", 274 | "text": [ 275 | "-490\n" 276 | ] 277 | } 278 | ], 279 | "source": [ 280 | "summ(10,-500)" 281 | ] 282 | }, 283 | { 284 | "cell_type": "code", 285 | "execution_count": 19, 286 | "metadata": {}, 287 | "outputs": [], 288 | "source": [ 289 | "def summation(num1,num2,num3):\n", 290 | " return num1+num2+num3" 291 | ] 292 | }, 293 | { 294 | "cell_type": "code", 295 | "execution_count": 20, 296 | "metadata": {}, 297 | "outputs": [ 298 | { 299 | "data": { 300 | "text/plain": [ 301 | "60" 302 | ] 303 | }, 304 | "execution_count": 20, 305 | "metadata": {}, 306 | "output_type": "execute_result" 307 | } 308 | ], 309 | "source": [ 310 | "summation(10,20,30)" 311 | ] 312 | }, 313 | { 314 | "cell_type": "code", 315 | "execution_count": 21, 316 | "metadata": {}, 317 | "outputs": [], 318 | "source": [ 319 | "my_result = summation(10,20,30)" 320 | ] 321 | }, 322 | { 323 | "cell_type": "code", 324 | "execution_count": 22, 325 | "metadata": {}, 326 | "outputs": [ 327 | { 328 | "data": { 329 | "text/plain": [ 330 | "60" 331 | ] 332 | }, 333 | "execution_count": 22, 334 | "metadata": {}, 335 | "output_type": "execute_result" 336 | } 337 | ], 338 | "source": [ 339 | "my_result" 340 | ] 341 | }, 342 | { 343 | "cell_type": "code", 344 | "execution_count": 23, 345 | "metadata": {}, 346 | "outputs": [ 347 | { 348 | "name": "stdout", 349 | "output_type": "stream", 350 | "text": [ 351 | "30\n" 352 | ] 353 | } 354 | ], 355 | "source": [ 356 | "my_integer = summ(10,20)" 357 | ] 358 | }, 359 | { 360 | "cell_type": "code", 361 | "execution_count": 24, 362 | "metadata": {}, 363 | "outputs": [], 364 | "source": [ 365 | "my_integer" 366 | ] 367 | }, 368 | { 369 | "cell_type": "code", 370 | "execution_count": 25, 371 | "metadata": {}, 372 | "outputs": [ 373 | { 374 | "data": { 375 | "text/plain": [ 376 | "NoneType" 377 | ] 378 | }, 379 | "execution_count": 25, 380 | "metadata": {}, 381 | "output_type": "execute_result" 382 | } 383 | ], 384 | "source": [ 385 | "type(my_integer)" 386 | ] 387 | }, 388 | { 389 | "cell_type": "code", 390 | "execution_count": 26, 391 | "metadata": {}, 392 | "outputs": [], 393 | "source": [ 394 | "def control_string(s):\n", 395 | " if s[0] == \"m\":\n", 396 | " print(\"mmm\")" 397 | ] 398 | }, 399 | { 400 | "cell_type": "code", 401 | "execution_count": 27, 402 | "metadata": {}, 403 | "outputs": [], 404 | "source": [ 405 | "control_string(\"paris\")" 406 | ] 407 | }, 408 | { 409 | "cell_type": "code", 410 | "execution_count": 28, 411 | "metadata": {}, 412 | "outputs": [ 413 | { 414 | "name": "stdout", 415 | "output_type": "stream", 416 | "text": [ 417 | "mmm\n" 418 | ] 419 | } 420 | ], 421 | "source": [ 422 | "control_string(\"metallica\")" 423 | ] 424 | }, 425 | { 426 | "cell_type": "code", 427 | "execution_count": 29, 428 | "metadata": {}, 429 | "outputs": [], 430 | "source": [ 431 | "def control_string(s):\n", 432 | " if s[0] == \"m\":\n", 433 | " print(s.capitalize())" 434 | ] 435 | }, 436 | { 437 | "cell_type": "code", 438 | "execution_count": 30, 439 | "metadata": {}, 440 | "outputs": [ 441 | { 442 | "name": "stdout", 443 | "output_type": "stream", 444 | "text": [ 445 | "Metallica\n" 446 | ] 447 | } 448 | ], 449 | "source": [ 450 | "control_string(\"metallica\")" 451 | ] 452 | }, 453 | { 454 | "cell_type": "code", 455 | "execution_count": 31, 456 | "metadata": {}, 457 | "outputs": [], 458 | "source": [ 459 | "control_string(\"amsterdam\")" 460 | ] 461 | }, 462 | { 463 | "cell_type": "markdown", 464 | "metadata": {}, 465 | "source": [ 466 | "## arbitrary arguments & key word arguments" 467 | ] 468 | }, 469 | { 470 | "cell_type": "code", 471 | "execution_count": 32, 472 | "metadata": {}, 473 | "outputs": [], 474 | "source": [ 475 | "def summation_2(*args):\n", 476 | " return sum(args)" 477 | ] 478 | }, 479 | { 480 | "cell_type": "code", 481 | "execution_count": 33, 482 | "metadata": {}, 483 | "outputs": [ 484 | { 485 | "data": { 486 | "text/plain": [ 487 | "60" 488 | ] 489 | }, 490 | "execution_count": 33, 491 | "metadata": {}, 492 | "output_type": "execute_result" 493 | } 494 | ], 495 | "source": [ 496 | "summation_2(10,20,30)" 497 | ] 498 | }, 499 | { 500 | "cell_type": "code", 501 | "execution_count": 34, 502 | "metadata": {}, 503 | "outputs": [ 504 | { 505 | "data": { 506 | "text/plain": [ 507 | "260" 508 | ] 509 | }, 510 | "execution_count": 34, 511 | "metadata": {}, 512 | "output_type": "execute_result" 513 | } 514 | ], 515 | "source": [ 516 | "summation_2(50,60,70,80)" 517 | ] 518 | }, 519 | { 520 | "cell_type": "code", 521 | "execution_count": 35, 522 | "metadata": {}, 523 | "outputs": [], 524 | "source": [ 525 | "def my_func(*args):\n", 526 | " print(args)" 527 | ] 528 | }, 529 | { 530 | "cell_type": "code", 531 | "execution_count": 36, 532 | "metadata": {}, 533 | "outputs": [ 534 | { 535 | "name": "stdout", 536 | "output_type": "stream", 537 | "text": [ 538 | "(10, 20)\n" 539 | ] 540 | } 541 | ], 542 | "source": [ 543 | "my_func(10,20)" 544 | ] 545 | }, 546 | { 547 | "cell_type": "code", 548 | "execution_count": 37, 549 | "metadata": {}, 550 | "outputs": [ 551 | { 552 | "name": "stdout", 553 | "output_type": "stream", 554 | "text": [ 555 | "('a', 'b', 1, 2)\n" 556 | ] 557 | } 558 | ], 559 | "source": [ 560 | "my_func(\"a\",\"b\",1,2)" 561 | ] 562 | }, 563 | { 564 | "cell_type": "code", 565 | "execution_count": 40, 566 | "metadata": {}, 567 | "outputs": [], 568 | "source": [ 569 | "#def my_func_2(*atil):\n", 570 | "# print(atil)" 571 | ] 572 | }, 573 | { 574 | "cell_type": "code", 575 | "execution_count": 41, 576 | "metadata": {}, 577 | "outputs": [], 578 | "source": [ 579 | "#my_func_2(\"at\",\"il\",1,2,3)" 580 | ] 581 | }, 582 | { 583 | "cell_type": "code", 584 | "execution_count": 42, 585 | "metadata": {}, 586 | "outputs": [], 587 | "source": [ 588 | "def example_func(**kwargs):\n", 589 | " print(kwargs)" 590 | ] 591 | }, 592 | { 593 | "cell_type": "code", 594 | "execution_count": 43, 595 | "metadata": {}, 596 | "outputs": [ 597 | { 598 | "name": "stdout", 599 | "output_type": "stream", 600 | "text": [ 601 | "{'run': 100, 'swim': 200, 'basketball': 300}\n" 602 | ] 603 | } 604 | ], 605 | "source": [ 606 | "example_func(run=100,swim=200,basketball=300)" 607 | ] 608 | }, 609 | { 610 | "cell_type": "code", 611 | "execution_count": 44, 612 | "metadata": {}, 613 | "outputs": [ 614 | { 615 | "name": "stdout", 616 | "output_type": "stream", 617 | "text": [ 618 | "{'a': 1, 'b': 2}\n" 619 | ] 620 | } 621 | ], 622 | "source": [ 623 | "example_func(a=1,b=2)" 624 | ] 625 | }, 626 | { 627 | "cell_type": "code", 628 | "execution_count": 45, 629 | "metadata": {}, 630 | "outputs": [], 631 | "source": [ 632 | "def keyword_func(**kwargs):\n", 633 | " if \"Metallica\" in kwargs:\n", 634 | " print(\"Heavy Metalll!\")\n", 635 | " else:\n", 636 | " print(\"Rock is dead!!\")" 637 | ] 638 | }, 639 | { 640 | "cell_type": "code", 641 | "execution_count": 49, 642 | "metadata": {}, 643 | "outputs": [ 644 | { 645 | "name": "stdout", 646 | "output_type": "stream", 647 | "text": [ 648 | "Heavy Metalll!\n" 649 | ] 650 | } 651 | ], 652 | "source": [ 653 | "keyword_func(Metallica=10,Madonna=5,Muslum=4)" 654 | ] 655 | }, 656 | { 657 | "cell_type": "code", 658 | "execution_count": 50, 659 | "metadata": {}, 660 | "outputs": [ 661 | { 662 | "name": "stdout", 663 | "output_type": "stream", 664 | "text": [ 665 | "Rock is dead!!\n" 666 | ] 667 | } 668 | ], 669 | "source": [ 670 | "keyword_func(Madonna=8,Mickey=4)" 671 | ] 672 | }, 673 | { 674 | "cell_type": "code", 675 | "execution_count": null, 676 | "metadata": {}, 677 | "outputs": [], 678 | "source": [] 679 | } 680 | ], 681 | "metadata": { 682 | "kernelspec": { 683 | "display_name": "Python 3", 684 | "language": "python", 685 | "name": "python3" 686 | }, 687 | "language_info": { 688 | "codemirror_mode": { 689 | "name": "ipython", 690 | "version": 3 691 | }, 692 | "file_extension": ".py", 693 | "mimetype": "text/x-python", 694 | "name": "python", 695 | "nbconvert_exporter": "python", 696 | "pygments_lexer": "ipython3", 697 | "version": "3.6.4" 698 | } 699 | }, 700 | "nbformat": 4, 701 | "nbformat_minor": 2 702 | } 703 | -------------------------------------------------------------------------------- /18-PracticalFunctions.ipynb: -------------------------------------------------------------------------------- 1 | { 2 | "cells": [ 3 | { 4 | "cell_type": "code", 5 | "execution_count": 1, 6 | "metadata": {}, 7 | "outputs": [], 8 | "source": [ 9 | "def divide(number):\n", 10 | " return number / 2" 11 | ] 12 | }, 13 | { 14 | "cell_type": "code", 15 | "execution_count": 2, 16 | "metadata": {}, 17 | "outputs": [ 18 | { 19 | "data": { 20 | "text/plain": [ 21 | "5.0" 22 | ] 23 | }, 24 | "execution_count": 2, 25 | "metadata": {}, 26 | "output_type": "execute_result" 27 | } 28 | ], 29 | "source": [ 30 | "divide(10)" 31 | ] 32 | }, 33 | { 34 | "cell_type": "code", 35 | "execution_count": 3, 36 | "metadata": {}, 37 | "outputs": [], 38 | "source": [ 39 | "my_list=[1,2,3,4,5,6,7,8]" 40 | ] 41 | }, 42 | { 43 | "cell_type": "code", 44 | "execution_count": 8, 45 | "metadata": {}, 46 | "outputs": [ 47 | { 48 | "name": "stdout", 49 | "output_type": "stream", 50 | "text": [ 51 | "[0.5, 1.0, 1.5, 2.0, 2.5, 3.0, 3.5, 4.0]\n" 52 | ] 53 | } 54 | ], 55 | "source": [ 56 | "my_new_list = []\n", 57 | "for num in my_list:\n", 58 | " my_new_list.append(divide(num))\n", 59 | "print(my_new_list) " 60 | ] 61 | }, 62 | { 63 | "cell_type": "markdown", 64 | "metadata": {}, 65 | "source": [ 66 | "## map" 67 | ] 68 | }, 69 | { 70 | "cell_type": "code", 71 | "execution_count": 11, 72 | "metadata": {}, 73 | "outputs": [ 74 | { 75 | "data": { 76 | "text/plain": [ 77 | "[0.5, 1.0, 1.5, 2.0, 2.5, 3.0, 3.5, 4.0]" 78 | ] 79 | }, 80 | "execution_count": 11, 81 | "metadata": {}, 82 | "output_type": "execute_result" 83 | } 84 | ], 85 | "source": [ 86 | "list(map(divide,my_list))" 87 | ] 88 | }, 89 | { 90 | "cell_type": "code", 91 | "execution_count": 15, 92 | "metadata": {}, 93 | "outputs": [], 94 | "source": [ 95 | "def control_string(string):\n", 96 | " return \"Metallica\" in string" 97 | ] 98 | }, 99 | { 100 | "cell_type": "code", 101 | "execution_count": 17, 102 | "metadata": {}, 103 | "outputs": [ 104 | { 105 | "data": { 106 | "text/plain": [ 107 | "True" 108 | ] 109 | }, 110 | "execution_count": 17, 111 | "metadata": {}, 112 | "output_type": "execute_result" 113 | } 114 | ], 115 | "source": [ 116 | "control_string(\"Metallica kdlfkd\")" 117 | ] 118 | }, 119 | { 120 | "cell_type": "code", 121 | "execution_count": 22, 122 | "metadata": {}, 123 | "outputs": [], 124 | "source": [ 125 | "my_artist_list = [\"Metallica\", \"Madonna\", \"Queen\", \"Megadeth\", \"Muslum\",\"Metallica2\"]" 126 | ] 127 | }, 128 | { 129 | "cell_type": "code", 130 | "execution_count": 23, 131 | "metadata": {}, 132 | "outputs": [ 133 | { 134 | "data": { 135 | "text/plain": [ 136 | "[True, False, False, False, False, True]" 137 | ] 138 | }, 139 | "execution_count": 23, 140 | "metadata": {}, 141 | "output_type": "execute_result" 142 | } 143 | ], 144 | "source": [ 145 | "list(map(control_string,my_artist_list))" 146 | ] 147 | }, 148 | { 149 | "cell_type": "markdown", 150 | "metadata": {}, 151 | "source": [ 152 | "## filter" 153 | ] 154 | }, 155 | { 156 | "cell_type": "code", 157 | "execution_count": 24, 158 | "metadata": {}, 159 | "outputs": [ 160 | { 161 | "data": { 162 | "text/plain": [ 163 | "['Metallica', 'Metallica2']" 164 | ] 165 | }, 166 | "execution_count": 24, 167 | "metadata": {}, 168 | "output_type": "execute_result" 169 | } 170 | ], 171 | "source": [ 172 | "list(filter(control_string,my_artist_list))" 173 | ] 174 | }, 175 | { 176 | "cell_type": "markdown", 177 | "metadata": {}, 178 | "source": [ 179 | "## lambda" 180 | ] 181 | }, 182 | { 183 | "cell_type": "code", 184 | "execution_count": 29, 185 | "metadata": {}, 186 | "outputs": [], 187 | "source": [ 188 | "multiply = lambda number:number * 3" 189 | ] 190 | }, 191 | { 192 | "cell_type": "code", 193 | "execution_count": 32, 194 | "metadata": {}, 195 | "outputs": [ 196 | { 197 | "data": { 198 | "text/plain": [ 199 | "15" 200 | ] 201 | }, 202 | "execution_count": 32, 203 | "metadata": {}, 204 | "output_type": "execute_result" 205 | } 206 | ], 207 | "source": [ 208 | "multiply(5)" 209 | ] 210 | }, 211 | { 212 | "cell_type": "code", 213 | "execution_count": 33, 214 | "metadata": {}, 215 | "outputs": [], 216 | "source": [ 217 | "my_list_3 = [3,5,7,9]" 218 | ] 219 | }, 220 | { 221 | "cell_type": "code", 222 | "execution_count": 34, 223 | "metadata": {}, 224 | "outputs": [ 225 | { 226 | "data": { 227 | "text/plain": [ 228 | "[12, 20, 28, 36]" 229 | ] 230 | }, 231 | "execution_count": 34, 232 | "metadata": {}, 233 | "output_type": "execute_result" 234 | } 235 | ], 236 | "source": [ 237 | "list(map(lambda num:num*4,my_list_3))" 238 | ] 239 | }, 240 | { 241 | "cell_type": "code", 242 | "execution_count": null, 243 | "metadata": {}, 244 | "outputs": [], 245 | "source": [] 246 | } 247 | ], 248 | "metadata": { 249 | "kernelspec": { 250 | "display_name": "Python 3", 251 | "language": "python", 252 | "name": "python3" 253 | }, 254 | "language_info": { 255 | "codemirror_mode": { 256 | "name": "ipython", 257 | "version": 3 258 | }, 259 | "file_extension": ".py", 260 | "mimetype": "text/x-python", 261 | "name": "python", 262 | "nbconvert_exporter": "python", 263 | "pygments_lexer": "ipython3", 264 | "version": "3.6.4" 265 | } 266 | }, 267 | "nbformat": 4, 268 | "nbformat_minor": 2 269 | } 270 | -------------------------------------------------------------------------------- /19-Scope.ipynb: -------------------------------------------------------------------------------- 1 | { 2 | "cells": [ 3 | { 4 | "cell_type": "code", 5 | "execution_count": 1, 6 | "metadata": {}, 7 | "outputs": [], 8 | "source": [ 9 | "number = 10\n", 10 | "\n", 11 | "def multiply(num):\n", 12 | " number = 5\n", 13 | " return num * number" 14 | ] 15 | }, 16 | { 17 | "cell_type": "code", 18 | "execution_count": 2, 19 | "metadata": {}, 20 | "outputs": [ 21 | { 22 | "data": { 23 | "text/plain": [ 24 | "50" 25 | ] 26 | }, 27 | "execution_count": 2, 28 | "metadata": {}, 29 | "output_type": "execute_result" 30 | } 31 | ], 32 | "source": [ 33 | "multiply(10)" 34 | ] 35 | }, 36 | { 37 | "cell_type": "code", 38 | "execution_count": 3, 39 | "metadata": {}, 40 | "outputs": [ 41 | { 42 | "name": "stdout", 43 | "output_type": "stream", 44 | "text": [ 45 | "10\n" 46 | ] 47 | } 48 | ], 49 | "source": [ 50 | "print(number)" 51 | ] 52 | }, 53 | { 54 | "cell_type": "code", 55 | "execution_count": 4, 56 | "metadata": {}, 57 | "outputs": [], 58 | "source": [ 59 | "a = 10\n", 60 | "a = 5" 61 | ] 62 | }, 63 | { 64 | "cell_type": "code", 65 | "execution_count": 5, 66 | "metadata": {}, 67 | "outputs": [ 68 | { 69 | "name": "stdout", 70 | "output_type": "stream", 71 | "text": [ 72 | "5\n" 73 | ] 74 | } 75 | ], 76 | "source": [ 77 | "print(a)" 78 | ] 79 | }, 80 | { 81 | "cell_type": "markdown", 82 | "metadata": {}, 83 | "source": [ 84 | "# LEGB \n", 85 | "\n", 86 | "# L -> Local\n", 87 | "# E -> Enclosing\n", 88 | "# G -> Global\n", 89 | "# B -> Built-in" 90 | ] 91 | }, 92 | { 93 | "cell_type": "code", 94 | "execution_count": 44, 95 | "metadata": {}, 96 | "outputs": [], 97 | "source": [ 98 | "my_string = \"Atil\"\n", 99 | "#Global\n", 100 | "\n", 101 | "def my_func():\n", 102 | " my_string = \"James\"\n", 103 | " #Enclosing\n", 104 | " \n", 105 | " def my_func_2():\n", 106 | " \n", 107 | " #Local\n", 108 | " my_string = \"Lars\"\n", 109 | " print(my_string)\n", 110 | " \n", 111 | " my_func_2()" 112 | ] 113 | }, 114 | { 115 | "cell_type": "code", 116 | "execution_count": 45, 117 | "metadata": {}, 118 | "outputs": [ 119 | { 120 | "name": "stdout", 121 | "output_type": "stream", 122 | "text": [ 123 | "Lars\n" 124 | ] 125 | } 126 | ], 127 | "source": [ 128 | "my_func()" 129 | ] 130 | }, 131 | { 132 | "cell_type": "code", 133 | "execution_count": 46, 134 | "metadata": {}, 135 | "outputs": [ 136 | { 137 | "data": { 138 | "text/plain": [ 139 | "'Atil'" 140 | ] 141 | }, 142 | "execution_count": 46, 143 | "metadata": {}, 144 | "output_type": "execute_result" 145 | } 146 | ], 147 | "source": [ 148 | "my_string" 149 | ] 150 | }, 151 | { 152 | "cell_type": "code", 153 | "execution_count": 53, 154 | "metadata": {}, 155 | "outputs": [], 156 | "source": [ 157 | "y = 10\n", 158 | "\n", 159 | "def func_new(y):\n", 160 | " print(y)\n", 161 | " y = 5\n", 162 | " print(y)\n", 163 | " return y" 164 | ] 165 | }, 166 | { 167 | "cell_type": "code", 168 | "execution_count": 54, 169 | "metadata": {}, 170 | "outputs": [ 171 | { 172 | "name": "stdout", 173 | "output_type": "stream", 174 | "text": [ 175 | "10\n", 176 | "5\n" 177 | ] 178 | }, 179 | { 180 | "data": { 181 | "text/plain": [ 182 | "5" 183 | ] 184 | }, 185 | "execution_count": 54, 186 | "metadata": {}, 187 | "output_type": "execute_result" 188 | } 189 | ], 190 | "source": [ 191 | "func_new(10)" 192 | ] 193 | }, 194 | { 195 | "cell_type": "code", 196 | "execution_count": 55, 197 | "metadata": {}, 198 | "outputs": [ 199 | { 200 | "name": "stdout", 201 | "output_type": "stream", 202 | "text": [ 203 | "10\n", 204 | "5\n" 205 | ] 206 | } 207 | ], 208 | "source": [ 209 | "y = func_new(y)" 210 | ] 211 | }, 212 | { 213 | "cell_type": "code", 214 | "execution_count": 56, 215 | "metadata": {}, 216 | "outputs": [ 217 | { 218 | "data": { 219 | "text/plain": [ 220 | "5" 221 | ] 222 | }, 223 | "execution_count": 56, 224 | "metadata": {}, 225 | "output_type": "execute_result" 226 | } 227 | ], 228 | "source": [ 229 | "y" 230 | ] 231 | }, 232 | { 233 | "cell_type": "code", 234 | "execution_count": 57, 235 | "metadata": {}, 236 | "outputs": [], 237 | "source": [ 238 | "y = 10\n", 239 | "\n", 240 | "def func_new():\n", 241 | " global y\n", 242 | " y = 5\n", 243 | " print(y)" 244 | ] 245 | }, 246 | { 247 | "cell_type": "code", 248 | "execution_count": 58, 249 | "metadata": {}, 250 | "outputs": [ 251 | { 252 | "name": "stdout", 253 | "output_type": "stream", 254 | "text": [ 255 | "5\n" 256 | ] 257 | } 258 | ], 259 | "source": [ 260 | "func_new()" 261 | ] 262 | }, 263 | { 264 | "cell_type": "code", 265 | "execution_count": 59, 266 | "metadata": {}, 267 | "outputs": [ 268 | { 269 | "data": { 270 | "text/plain": [ 271 | "5" 272 | ] 273 | }, 274 | "execution_count": 59, 275 | "metadata": {}, 276 | "output_type": "execute_result" 277 | } 278 | ], 279 | "source": [ 280 | "y" 281 | ] 282 | }, 283 | { 284 | "cell_type": "code", 285 | "execution_count": null, 286 | "metadata": {}, 287 | "outputs": [], 288 | "source": [] 289 | } 290 | ], 291 | "metadata": { 292 | "kernelspec": { 293 | "display_name": "Python 3", 294 | "language": "python", 295 | "name": "python3" 296 | }, 297 | "language_info": { 298 | "codemirror_mode": { 299 | "name": "ipython", 300 | "version": 3 301 | }, 302 | "file_extension": ".py", 303 | "mimetype": "text/x-python", 304 | "name": "python", 305 | "nbconvert_exporter": "python", 306 | "pygments_lexer": "ipython3", 307 | "version": "3.6.4" 308 | } 309 | }, 310 | "nbformat": 4, 311 | "nbformat_minor": 2 312 | } 313 | -------------------------------------------------------------------------------- /20-Hangman.py: -------------------------------------------------------------------------------- 1 | name = input("Enter name: ") 2 | print("Hello " + name + " time to play hangman!") 3 | 4 | secret_word = "Metallica" 5 | 6 | guess_string = "" 7 | 8 | lives = 10 9 | 10 | while lives > 0: 11 | 12 | character_left = 0 13 | 14 | for character in secret_word: 15 | 16 | if character in guess_string: 17 | 18 | print(character) 19 | else: 20 | print("-") 21 | character_left += 1 22 | 23 | if character_left == 0: 24 | print("You won!!!") 25 | break 26 | 27 | 28 | guess = input("Guess a word: ") 29 | guess_string += guess 30 | 31 | if guess not in secret_word: 32 | lives -= 1 33 | print("Wrong!") 34 | print(f"You have {lives} left") 35 | 36 | if lives == 0: 37 | print("You died!") 38 | 39 | -------------------------------------------------------------------------------- /21-Decorators.ipynb: -------------------------------------------------------------------------------- 1 | { 2 | "cells": [ 3 | { 4 | "cell_type": "code", 5 | "execution_count": 1, 6 | "metadata": {}, 7 | "outputs": [], 8 | "source": [ 9 | "def func(new_func):\n", 10 | " print(\"func started\")\n", 11 | " new_func()\n", 12 | " print(\"func ended\")" 13 | ] 14 | }, 15 | { 16 | "cell_type": "code", 17 | "execution_count": 2, 18 | "metadata": {}, 19 | "outputs": [], 20 | "source": [ 21 | "def hello_func():\n", 22 | " print(\"hello world\")" 23 | ] 24 | }, 25 | { 26 | "cell_type": "code", 27 | "execution_count": 3, 28 | "metadata": {}, 29 | "outputs": [ 30 | { 31 | "name": "stdout", 32 | "output_type": "stream", 33 | "text": [ 34 | "func started\n", 35 | "hello world\n", 36 | "func ended\n" 37 | ] 38 | } 39 | ], 40 | "source": [ 41 | "func(hello_func)" 42 | ] 43 | }, 44 | { 45 | "cell_type": "code", 46 | "execution_count": 14, 47 | "metadata": {}, 48 | "outputs": [], 49 | "source": [ 50 | "def new_func():\n", 51 | " print(\"new func\")\n", 52 | " def new_func_2():\n", 53 | " print(\"new func 2\")\n", 54 | " return new_func_2" 55 | ] 56 | }, 57 | { 58 | "cell_type": "code", 59 | "execution_count": 15, 60 | "metadata": {}, 61 | "outputs": [ 62 | { 63 | "name": "stdout", 64 | "output_type": "stream", 65 | "text": [ 66 | "new func\n" 67 | ] 68 | }, 69 | { 70 | "data": { 71 | "text/plain": [ 72 | ".new_func_2>" 73 | ] 74 | }, 75 | "execution_count": 15, 76 | "metadata": {}, 77 | "output_type": "execute_result" 78 | } 79 | ], 80 | "source": [ 81 | "new_func()" 82 | ] 83 | }, 84 | { 85 | "cell_type": "code", 86 | "execution_count": 16, 87 | "metadata": {}, 88 | "outputs": [ 89 | { 90 | "name": "stdout", 91 | "output_type": "stream", 92 | "text": [ 93 | "new func\n" 94 | ] 95 | } 96 | ], 97 | "source": [ 98 | "new_string = new_func()" 99 | ] 100 | }, 101 | { 102 | "cell_type": "code", 103 | "execution_count": 17, 104 | "metadata": {}, 105 | "outputs": [ 106 | { 107 | "name": "stdout", 108 | "output_type": "stream", 109 | "text": [ 110 | "new func 2\n" 111 | ] 112 | } 113 | ], 114 | "source": [ 115 | "new_string()" 116 | ] 117 | }, 118 | { 119 | "cell_type": "code", 120 | "execution_count": 19, 121 | "metadata": {}, 122 | "outputs": [], 123 | "source": [ 124 | "def decorator_function(func):\n", 125 | " \n", 126 | " def wrapper_function():\n", 127 | " \n", 128 | " print(\"wrapper started\")\n", 129 | " \n", 130 | " func()\n", 131 | " \n", 132 | " print(\"wrapper stopped\")\n", 133 | " \n", 134 | " return wrapper_function" 135 | ] 136 | }, 137 | { 138 | "cell_type": "code", 139 | "execution_count": 21, 140 | "metadata": {}, 141 | "outputs": [], 142 | "source": [ 143 | "def func_new():\n", 144 | " print(\"hello world\")" 145 | ] 146 | }, 147 | { 148 | "cell_type": "code", 149 | "execution_count": 23, 150 | "metadata": {}, 151 | "outputs": [], 152 | "source": [ 153 | "example_function = decorator_function(func_new)" 154 | ] 155 | }, 156 | { 157 | "cell_type": "code", 158 | "execution_count": 25, 159 | "metadata": {}, 160 | "outputs": [ 161 | { 162 | "name": "stdout", 163 | "output_type": "stream", 164 | "text": [ 165 | "wrapper started\n", 166 | "hello world\n", 167 | "wrapper stopped\n" 168 | ] 169 | } 170 | ], 171 | "source": [ 172 | "example_function()" 173 | ] 174 | }, 175 | { 176 | "cell_type": "code", 177 | "execution_count": 30, 178 | "metadata": {}, 179 | "outputs": [], 180 | "source": [ 181 | "@decorator_function\n", 182 | "def func_new():\n", 183 | " print(\"hello world\")" 184 | ] 185 | }, 186 | { 187 | "cell_type": "code", 188 | "execution_count": 31, 189 | "metadata": {}, 190 | "outputs": [ 191 | { 192 | "name": "stdout", 193 | "output_type": "stream", 194 | "text": [ 195 | "wrapper started\n", 196 | "hello world\n", 197 | "wrapper stopped\n" 198 | ] 199 | } 200 | ], 201 | "source": [ 202 | "func_new()" 203 | ] 204 | }, 205 | { 206 | "cell_type": "code", 207 | "execution_count": null, 208 | "metadata": {}, 209 | "outputs": [], 210 | "source": [] 211 | } 212 | ], 213 | "metadata": { 214 | "kernelspec": { 215 | "display_name": "Python 3", 216 | "language": "python", 217 | "name": "python3" 218 | }, 219 | "language_info": { 220 | "codemirror_mode": { 221 | "name": "ipython", 222 | "version": 3 223 | }, 224 | "file_extension": ".py", 225 | "mimetype": "text/x-python", 226 | "name": "python", 227 | "nbconvert_exporter": "python", 228 | "pygments_lexer": "ipython3", 229 | "version": "3.6.4" 230 | } 231 | }, 232 | "nbformat": 4, 233 | "nbformat_minor": 2 234 | } 235 | -------------------------------------------------------------------------------- /22-Calculator.py: -------------------------------------------------------------------------------- 1 | 2 | def calc(x, y, ops): 3 | 4 | if ops not in '+-/*': 5 | return 'Choose operator: "+, -, *, /"!' 6 | 7 | if ops == '+': 8 | return(str(x) + ' ' + ops + ' ' + str(y) + ' = ' + str(x + y)) 9 | if ops == '-': 10 | return(str(x) + ' ' + ops + ' ' + str(y) + ' = ' + str(x - y)) 11 | if ops == '*': 12 | return(str(x) + ' ' + ops + ' ' + str(y) + ' = ' + str(x * y)) 13 | if ops == '/': 14 | return(str(x) + ' ' + ops + ' ' + str(y) + ' = ' + str(x / y)) 15 | 16 | while True: 17 | 18 | x = int(input('Enter first number: ')) 19 | y = int(input('Enter second number: ')) 20 | ops = input("Choose between +, -, *, / ") 21 | 22 | print(calc(x, y, ops)) 23 | 24 | -------------------------------------------------------------------------------- /23-OOPClasses.ipynb: -------------------------------------------------------------------------------- 1 | { 2 | "cells": [ 3 | { 4 | "cell_type": "markdown", 5 | "metadata": {}, 6 | "source": [ 7 | "## class" 8 | ] 9 | }, 10 | { 11 | "cell_type": "code", 12 | "execution_count": 1, 13 | "metadata": {}, 14 | "outputs": [], 15 | "source": [ 16 | "my_list = list()" 17 | ] 18 | }, 19 | { 20 | "cell_type": "markdown", 21 | "metadata": {}, 22 | "source": [ 23 | "# instance & attribute" 24 | ] 25 | }, 26 | { 27 | "cell_type": "code", 28 | "execution_count": 2, 29 | "metadata": {}, 30 | "outputs": [], 31 | "source": [ 32 | "# snake= my_string\n", 33 | "# camel= myString" 34 | ] 35 | }, 36 | { 37 | "cell_type": "code", 38 | "execution_count": 52, 39 | "metadata": {}, 40 | "outputs": [], 41 | "source": [ 42 | "class Musician():\n", 43 | " \n", 44 | " job = \"musician\"\n", 45 | " \n", 46 | " def __init__(self,name,age,instrument):\n", 47 | " self.name = name\n", 48 | " self.age = age\n", 49 | " self.instrument = instrument\n", 50 | " \n", 51 | " #Method\n", 52 | " \n", 53 | " def sing(self):\n", 54 | " print(f\"We are the champions! {self.instrument}\")" 55 | ] 56 | }, 57 | { 58 | "cell_type": "code", 59 | "execution_count": 53, 60 | "metadata": {}, 61 | "outputs": [], 62 | "source": [ 63 | "my_musician = Musician(\"James\", 50, \"Guitar\")" 64 | ] 65 | }, 66 | { 67 | "cell_type": "code", 68 | "execution_count": 54, 69 | "metadata": {}, 70 | "outputs": [ 71 | { 72 | "data": { 73 | "text/plain": [ 74 | "50" 75 | ] 76 | }, 77 | "execution_count": 54, 78 | "metadata": {}, 79 | "output_type": "execute_result" 80 | } 81 | ], 82 | "source": [ 83 | "my_musician.age" 84 | ] 85 | }, 86 | { 87 | "cell_type": "code", 88 | "execution_count": 55, 89 | "metadata": {}, 90 | "outputs": [ 91 | { 92 | "data": { 93 | "text/plain": [ 94 | "'James'" 95 | ] 96 | }, 97 | "execution_count": 55, 98 | "metadata": {}, 99 | "output_type": "execute_result" 100 | } 101 | ], 102 | "source": [ 103 | "my_musician.name" 104 | ] 105 | }, 106 | { 107 | "cell_type": "code", 108 | "execution_count": 56, 109 | "metadata": {}, 110 | "outputs": [ 111 | { 112 | "data": { 113 | "text/plain": [ 114 | "'Guitar'" 115 | ] 116 | }, 117 | "execution_count": 56, 118 | "metadata": {}, 119 | "output_type": "execute_result" 120 | } 121 | ], 122 | "source": [ 123 | "my_musician.instrument" 124 | ] 125 | }, 126 | { 127 | "cell_type": "code", 128 | "execution_count": 57, 129 | "metadata": {}, 130 | "outputs": [], 131 | "source": [ 132 | "my_musician.job = \"singer\"" 133 | ] 134 | }, 135 | { 136 | "cell_type": "code", 137 | "execution_count": 58, 138 | "metadata": {}, 139 | "outputs": [ 140 | { 141 | "data": { 142 | "text/plain": [ 143 | "'singer'" 144 | ] 145 | }, 146 | "execution_count": 58, 147 | "metadata": {}, 148 | "output_type": "execute_result" 149 | } 150 | ], 151 | "source": [ 152 | "my_musician.job" 153 | ] 154 | }, 155 | { 156 | "cell_type": "code", 157 | "execution_count": 59, 158 | "metadata": {}, 159 | "outputs": [ 160 | { 161 | "name": "stdout", 162 | "output_type": "stream", 163 | "text": [ 164 | "We are the champions! Guitar\n" 165 | ] 166 | } 167 | ], 168 | "source": [ 169 | "my_musician.sing()" 170 | ] 171 | }, 172 | { 173 | "cell_type": "code", 174 | "execution_count": 76, 175 | "metadata": {}, 176 | "outputs": [], 177 | "source": [ 178 | "class DogYears():\n", 179 | " \n", 180 | " year_factor = 7\n", 181 | " \n", 182 | " def __init__(self,age=5):\n", 183 | " self.age = age\n", 184 | " self.age_multiplied = age * 7\n", 185 | " \n", 186 | " def calculation(self):\n", 187 | " return self.age * DogYears.year_factor" 188 | ] 189 | }, 190 | { 191 | "cell_type": "code", 192 | "execution_count": 77, 193 | "metadata": {}, 194 | "outputs": [], 195 | "source": [ 196 | "my_dog = DogYears()" 197 | ] 198 | }, 199 | { 200 | "cell_type": "code", 201 | "execution_count": 78, 202 | "metadata": {}, 203 | "outputs": [ 204 | { 205 | "data": { 206 | "text/plain": [ 207 | "35" 208 | ] 209 | }, 210 | "execution_count": 78, 211 | "metadata": {}, 212 | "output_type": "execute_result" 213 | } 214 | ], 215 | "source": [ 216 | "my_dog.calculation()" 217 | ] 218 | }, 219 | { 220 | "cell_type": "code", 221 | "execution_count": 79, 222 | "metadata": {}, 223 | "outputs": [ 224 | { 225 | "data": { 226 | "text/plain": [ 227 | "35" 228 | ] 229 | }, 230 | "execution_count": 79, 231 | "metadata": {}, 232 | "output_type": "execute_result" 233 | } 234 | ], 235 | "source": [ 236 | "my_dog.age_multiplied" 237 | ] 238 | }, 239 | { 240 | "cell_type": "markdown", 241 | "metadata": {}, 242 | "source": [ 243 | "# inheritance" 244 | ] 245 | }, 246 | { 247 | "cell_type": "code", 248 | "execution_count": 80, 249 | "metadata": {}, 250 | "outputs": [], 251 | "source": [ 252 | "class Class1():\n", 253 | " \n", 254 | " def __init__(self):\n", 255 | " print(\"Class 1 created\")\n", 256 | " \n", 257 | " def method_1(self):\n", 258 | " print(\"method 1\")\n", 259 | " \n", 260 | " def method_2(self):\n", 261 | " print(\"method 2\")" 262 | ] 263 | }, 264 | { 265 | "cell_type": "code", 266 | "execution_count": 81, 267 | "metadata": {}, 268 | "outputs": [ 269 | { 270 | "name": "stdout", 271 | "output_type": "stream", 272 | "text": [ 273 | "Class 1 created\n" 274 | ] 275 | } 276 | ], 277 | "source": [ 278 | "my_instance = Class1()" 279 | ] 280 | }, 281 | { 282 | "cell_type": "code", 283 | "execution_count": 82, 284 | "metadata": {}, 285 | "outputs": [ 286 | { 287 | "name": "stdout", 288 | "output_type": "stream", 289 | "text": [ 290 | "method 1\n" 291 | ] 292 | } 293 | ], 294 | "source": [ 295 | "my_instance.method_1()" 296 | ] 297 | }, 298 | { 299 | "cell_type": "code", 300 | "execution_count": 83, 301 | "metadata": {}, 302 | "outputs": [ 303 | { 304 | "name": "stdout", 305 | "output_type": "stream", 306 | "text": [ 307 | "method 2\n" 308 | ] 309 | } 310 | ], 311 | "source": [ 312 | "my_instance.method_2()" 313 | ] 314 | }, 315 | { 316 | "cell_type": "code", 317 | "execution_count": 91, 318 | "metadata": {}, 319 | "outputs": [], 320 | "source": [ 321 | "class Class2(Class1):\n", 322 | " \n", 323 | " def __init__(self):\n", 324 | " Class1.__init__(self)\n", 325 | " print(\"Class 2 created\")\n", 326 | " \n", 327 | " def method_3(self):\n", 328 | " print(\"method 3\")\n", 329 | " \n", 330 | " #override\n", 331 | " \n", 332 | " def method_1(self):\n", 333 | " print(\"method 1 override\")" 334 | ] 335 | }, 336 | { 337 | "cell_type": "code", 338 | "execution_count": 92, 339 | "metadata": {}, 340 | "outputs": [ 341 | { 342 | "name": "stdout", 343 | "output_type": "stream", 344 | "text": [ 345 | "Class 1 created\n", 346 | "Class 2 created\n" 347 | ] 348 | } 349 | ], 350 | "source": [ 351 | "my_instance_2 = Class2()" 352 | ] 353 | }, 354 | { 355 | "cell_type": "code", 356 | "execution_count": 93, 357 | "metadata": {}, 358 | "outputs": [ 359 | { 360 | "name": "stdout", 361 | "output_type": "stream", 362 | "text": [ 363 | "method 2\n" 364 | ] 365 | } 366 | ], 367 | "source": [ 368 | "my_instance_2.method_2()" 369 | ] 370 | }, 371 | { 372 | "cell_type": "code", 373 | "execution_count": 94, 374 | "metadata": {}, 375 | "outputs": [ 376 | { 377 | "name": "stdout", 378 | "output_type": "stream", 379 | "text": [ 380 | "method 3\n" 381 | ] 382 | } 383 | ], 384 | "source": [ 385 | "my_instance_2.method_3()" 386 | ] 387 | }, 388 | { 389 | "cell_type": "code", 390 | "execution_count": 96, 391 | "metadata": {}, 392 | "outputs": [ 393 | { 394 | "name": "stdout", 395 | "output_type": "stream", 396 | "text": [ 397 | "method 1 override\n" 398 | ] 399 | } 400 | ], 401 | "source": [ 402 | "my_instance_2.method_1()" 403 | ] 404 | }, 405 | { 406 | "cell_type": "code", 407 | "execution_count": 97, 408 | "metadata": {}, 409 | "outputs": [ 410 | { 411 | "name": "stdout", 412 | "output_type": "stream", 413 | "text": [ 414 | "method 1\n" 415 | ] 416 | } 417 | ], 418 | "source": [ 419 | "my_instance.method_1()" 420 | ] 421 | }, 422 | { 423 | "cell_type": "markdown", 424 | "metadata": {}, 425 | "source": [ 426 | "# Polymorphism" 427 | ] 428 | }, 429 | { 430 | "cell_type": "code", 431 | "execution_count": 98, 432 | "metadata": {}, 433 | "outputs": [], 434 | "source": [ 435 | "class Apple():\n", 436 | " \n", 437 | " def __init__(self,name):\n", 438 | " self.name = name\n", 439 | " \n", 440 | " def information(self):\n", 441 | " return self.name + \" 100 calories\"" 442 | ] 443 | }, 444 | { 445 | "cell_type": "code", 446 | "execution_count": 99, 447 | "metadata": {}, 448 | "outputs": [], 449 | "source": [ 450 | "class Banana():\n", 451 | " \n", 452 | " def __init__(self,name):\n", 453 | " self.name = name\n", 454 | " \n", 455 | " def information(self):\n", 456 | " return self.name + \" 200 calories\"" 457 | ] 458 | }, 459 | { 460 | "cell_type": "code", 461 | "execution_count": 100, 462 | "metadata": {}, 463 | "outputs": [], 464 | "source": [ 465 | "banana = Banana(\"banana\")" 466 | ] 467 | }, 468 | { 469 | "cell_type": "code", 470 | "execution_count": 101, 471 | "metadata": {}, 472 | "outputs": [], 473 | "source": [ 474 | "apple = Apple(\"apple\")" 475 | ] 476 | }, 477 | { 478 | "cell_type": "code", 479 | "execution_count": 102, 480 | "metadata": {}, 481 | "outputs": [ 482 | { 483 | "data": { 484 | "text/plain": [ 485 | "'banana 200 calories'" 486 | ] 487 | }, 488 | "execution_count": 102, 489 | "metadata": {}, 490 | "output_type": "execute_result" 491 | } 492 | ], 493 | "source": [ 494 | "banana.information()" 495 | ] 496 | }, 497 | { 498 | "cell_type": "code", 499 | "execution_count": 103, 500 | "metadata": {}, 501 | "outputs": [ 502 | { 503 | "data": { 504 | "text/plain": [ 505 | "'apple 100 calories'" 506 | ] 507 | }, 508 | "execution_count": 103, 509 | "metadata": {}, 510 | "output_type": "execute_result" 511 | } 512 | ], 513 | "source": [ 514 | "apple.information()" 515 | ] 516 | }, 517 | { 518 | "cell_type": "code", 519 | "execution_count": 104, 520 | "metadata": {}, 521 | "outputs": [], 522 | "source": [ 523 | "fruit_list = [banana,apple]" 524 | ] 525 | }, 526 | { 527 | "cell_type": "code", 528 | "execution_count": 105, 529 | "metadata": {}, 530 | "outputs": [ 531 | { 532 | "name": "stdout", 533 | "output_type": "stream", 534 | "text": [ 535 | "banana 200 calories\n", 536 | "apple 100 calories\n" 537 | ] 538 | } 539 | ], 540 | "source": [ 541 | "for fruit in fruit_list:\n", 542 | " print(fruit.information())" 543 | ] 544 | }, 545 | { 546 | "cell_type": "code", 547 | "execution_count": 106, 548 | "metadata": {}, 549 | "outputs": [], 550 | "source": [ 551 | "def get_info(fruit):\n", 552 | " print(fruit.information())" 553 | ] 554 | }, 555 | { 556 | "cell_type": "code", 557 | "execution_count": 107, 558 | "metadata": {}, 559 | "outputs": [ 560 | { 561 | "name": "stdout", 562 | "output_type": "stream", 563 | "text": [ 564 | "banana 200 calories\n" 565 | ] 566 | } 567 | ], 568 | "source": [ 569 | "get_info(banana)" 570 | ] 571 | }, 572 | { 573 | "cell_type": "code", 574 | "execution_count": 108, 575 | "metadata": {}, 576 | "outputs": [ 577 | { 578 | "name": "stdout", 579 | "output_type": "stream", 580 | "text": [ 581 | "apple 100 calories\n" 582 | ] 583 | } 584 | ], 585 | "source": [ 586 | "get_info(apple)" 587 | ] 588 | }, 589 | { 590 | "cell_type": "code", 591 | "execution_count": null, 592 | "metadata": {}, 593 | "outputs": [], 594 | "source": [] 595 | } 596 | ], 597 | "metadata": { 598 | "kernelspec": { 599 | "display_name": "Python 3", 600 | "language": "python", 601 | "name": "python3" 602 | }, 603 | "language_info": { 604 | "codemirror_mode": { 605 | "name": "ipython", 606 | "version": 3 607 | }, 608 | "file_extension": ".py", 609 | "mimetype": "text/x-python", 610 | "name": "python", 611 | "nbconvert_exporter": "python", 612 | "pygments_lexer": "ipython3", 613 | "version": "3.6.4" 614 | } 615 | }, 616 | "nbformat": 4, 617 | "nbformat_minor": 2 618 | } 619 | -------------------------------------------------------------------------------- /24-SpecialMethods.ipynb: -------------------------------------------------------------------------------- 1 | { 2 | "cells": [ 3 | { 4 | "cell_type": "code", 5 | "execution_count": 23, 6 | "metadata": {}, 7 | "outputs": [], 8 | "source": [ 9 | "class Fruits():\n", 10 | " \n", 11 | " def __init__(self,name,calories):\n", 12 | " self.name = name\n", 13 | " self.calories = calories\n", 14 | " \n", 15 | " def __str__(self):\n", 16 | " return f\"{self.name} has {self.calories}\"\n", 17 | " \n", 18 | " def __len__(self):\n", 19 | " return self.calories" 20 | ] 21 | }, 22 | { 23 | "cell_type": "code", 24 | "execution_count": 24, 25 | "metadata": {}, 26 | "outputs": [], 27 | "source": [ 28 | "my_fruit = Fruits(\"Banana\",200)" 29 | ] 30 | }, 31 | { 32 | "cell_type": "code", 33 | "execution_count": 25, 34 | "metadata": {}, 35 | "outputs": [ 36 | { 37 | "name": "stdout", 38 | "output_type": "stream", 39 | "text": [ 40 | "Banana has 200\n" 41 | ] 42 | } 43 | ], 44 | "source": [ 45 | "print(my_fruit)" 46 | ] 47 | }, 48 | { 49 | "cell_type": "code", 50 | "execution_count": 26, 51 | "metadata": {}, 52 | "outputs": [], 53 | "source": [ 54 | "my_list = [\"a\",\"b\",3]" 55 | ] 56 | }, 57 | { 58 | "cell_type": "code", 59 | "execution_count": 27, 60 | "metadata": {}, 61 | "outputs": [ 62 | { 63 | "name": "stdout", 64 | "output_type": "stream", 65 | "text": [ 66 | "['a', 'b', 3]\n" 67 | ] 68 | } 69 | ], 70 | "source": [ 71 | "print(my_list)" 72 | ] 73 | }, 74 | { 75 | "cell_type": "code", 76 | "execution_count": 28, 77 | "metadata": {}, 78 | "outputs": [ 79 | { 80 | "data": { 81 | "text/plain": [ 82 | "3" 83 | ] 84 | }, 85 | "execution_count": 28, 86 | "metadata": {}, 87 | "output_type": "execute_result" 88 | } 89 | ], 90 | "source": [ 91 | "len(my_list)" 92 | ] 93 | }, 94 | { 95 | "cell_type": "code", 96 | "execution_count": 29, 97 | "metadata": {}, 98 | "outputs": [ 99 | { 100 | "data": { 101 | "text/plain": [ 102 | "200" 103 | ] 104 | }, 105 | "execution_count": 29, 106 | "metadata": {}, 107 | "output_type": "execute_result" 108 | } 109 | ], 110 | "source": [ 111 | "len(my_fruit)" 112 | ] 113 | }, 114 | { 115 | "cell_type": "code", 116 | "execution_count": null, 117 | "metadata": {}, 118 | "outputs": [], 119 | "source": [] 120 | } 121 | ], 122 | "metadata": { 123 | "kernelspec": { 124 | "display_name": "Python 3", 125 | "language": "python", 126 | "name": "python3" 127 | }, 128 | "language_info": { 129 | "codemirror_mode": { 130 | "name": "ipython", 131 | "version": 3 132 | }, 133 | "file_extension": ".py", 134 | "mimetype": "text/x-python", 135 | "name": "python", 136 | "nbconvert_exporter": "python", 137 | "pygments_lexer": "ipython3", 138 | "version": "3.6.4" 139 | } 140 | }, 141 | "nbformat": 4, 142 | "nbformat_minor": 2 143 | } 144 | -------------------------------------------------------------------------------- /25-ModulesPackages.ipynb: -------------------------------------------------------------------------------- 1 | { 2 | "cells": [ 3 | { 4 | "cell_type": "code", 5 | "execution_count": 3, 6 | "metadata": {}, 7 | "outputs": [ 8 | { 9 | "data": { 10 | "text/plain": [ 11 | "79.79504953164854" 12 | ] 13 | }, 14 | "execution_count": 3, 15 | "metadata": {}, 16 | "output_type": "execute_result" 17 | } 18 | ], 19 | "source": [ 20 | "import numpy as np\n", 21 | "import matplotlib.pyplot as matplot\n", 22 | "\n", 23 | "grades = np.random.normal(80,30,1000)\n", 24 | "np.mean(grades)" 25 | ] 26 | }, 27 | { 28 | "cell_type": "code", 29 | "execution_count": 4, 30 | "metadata": {}, 31 | "outputs": [ 32 | { 33 | "data": { 34 | "image/png": "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\n", 35 | "text/plain": [ 36 | "" 37 | ] 38 | }, 39 | "metadata": {}, 40 | "output_type": "display_data" 41 | } 42 | ], 43 | "source": [ 44 | "matplot.hist(grades,50)\n", 45 | "matplot.show()" 46 | ] 47 | }, 48 | { 49 | "cell_type": "code", 50 | "execution_count": null, 51 | "metadata": {}, 52 | "outputs": [], 53 | "source": [] 54 | } 55 | ], 56 | "metadata": { 57 | "kernelspec": { 58 | "display_name": "Python 3", 59 | "language": "python", 60 | "name": "python3" 61 | }, 62 | "language_info": { 63 | "codemirror_mode": { 64 | "name": "ipython", 65 | "version": 3 66 | }, 67 | "file_extension": ".py", 68 | "mimetype": "text/x-python", 69 | "name": "python", 70 | "nbconvert_exporter": "python", 71 | "pygments_lexer": "ipython3", 72 | "version": "3.6.4" 73 | } 74 | }, 75 | "nbformat": 4, 76 | "nbformat_minor": 2 77 | } 78 | -------------------------------------------------------------------------------- /26-yoda.py: -------------------------------------------------------------------------------- 1 | 2 | def func_direct(): 3 | print("yoda direct") 4 | 5 | def func_imported(): 6 | print("yoda imported") 7 | 8 | 9 | if __name__ == '__main__': 10 | func_direct() 11 | else: 12 | func_imported() -------------------------------------------------------------------------------- /27-anakin.py: -------------------------------------------------------------------------------- 1 | import yoda 2 | 3 | print("anakin") -------------------------------------------------------------------------------- /28-ErrorHandling.ipynb: -------------------------------------------------------------------------------- 1 | { 2 | "cells": [ 3 | { 4 | "cell_type": "code", 5 | "execution_count": 1, 6 | "metadata": {}, 7 | "outputs": [], 8 | "source": [ 9 | "def summation(num1,num2):\n", 10 | " return num1 + num2" 11 | ] 12 | }, 13 | { 14 | "cell_type": "code", 15 | "execution_count": 8, 16 | "metadata": {}, 17 | "outputs": [ 18 | { 19 | "name": "stdout", 20 | "output_type": "stream", 21 | "text": [ 22 | "Enter number: james\n" 23 | ] 24 | } 25 | ], 26 | "source": [ 27 | "x = input(\"Enter number: \")" 28 | ] 29 | }, 30 | { 31 | "cell_type": "code", 32 | "execution_count": 9, 33 | "metadata": {}, 34 | "outputs": [ 35 | { 36 | "name": "stdout", 37 | "output_type": "stream", 38 | "text": [ 39 | "Enter number: 20\n" 40 | ] 41 | } 42 | ], 43 | "source": [ 44 | "y = input(\"Enter number: \")" 45 | ] 46 | }, 47 | { 48 | "cell_type": "code", 49 | "execution_count": 11, 50 | "metadata": {}, 51 | "outputs": [], 52 | "source": [ 53 | "def numberpower(num1):\n", 54 | " return num1 ** 2" 55 | ] 56 | }, 57 | { 58 | "cell_type": "markdown", 59 | "metadata": {}, 60 | "source": [ 61 | "# try, except, finally" 62 | ] 63 | }, 64 | { 65 | "cell_type": "code", 66 | "execution_count": 22, 67 | "metadata": {}, 68 | "outputs": [ 69 | { 70 | "name": "stdout", 71 | "output_type": "stream", 72 | "text": [ 73 | "Enter a number: james\n", 74 | "Enter a number!!!\n", 75 | "finally\n", 76 | "Enter a number: lars\n", 77 | "Enter a number!!!\n", 78 | "finally\n", 79 | "Enter a number: -10\n", 80 | "OK\n", 81 | "finally\n" 82 | ] 83 | } 84 | ], 85 | "source": [ 86 | "while True:\n", 87 | " try:\n", 88 | " my_int = int(input(\"Enter a number: \"))\n", 89 | " except:\n", 90 | " print(\"Enter a number!!!\")\n", 91 | " continue\n", 92 | " else:\n", 93 | " print(\"OK\")\n", 94 | " break\n", 95 | " finally:\n", 96 | " print(\"finally\")" 97 | ] 98 | }, 99 | { 100 | "cell_type": "code", 101 | "execution_count": null, 102 | "metadata": {}, 103 | "outputs": [], 104 | "source": [] 105 | }, 106 | { 107 | "cell_type": "code", 108 | "execution_count": null, 109 | "metadata": {}, 110 | "outputs": [], 111 | "source": [] 112 | }, 113 | { 114 | "cell_type": "code", 115 | "execution_count": null, 116 | "metadata": {}, 117 | "outputs": [], 118 | "source": [] 119 | } 120 | ], 121 | "metadata": { 122 | "kernelspec": { 123 | "display_name": "Python 3", 124 | "language": "python", 125 | "name": "python3" 126 | }, 127 | "language_info": { 128 | "codemirror_mode": { 129 | "name": "ipython", 130 | "version": 3 131 | }, 132 | "file_extension": ".py", 133 | "mimetype": "text/x-python", 134 | "name": "python", 135 | "nbconvert_exporter": "python", 136 | "pygments_lexer": "ipython3", 137 | "version": "3.6.4" 138 | } 139 | }, 140 | "nbformat": 4, 141 | "nbformat_minor": 2 142 | } 143 | -------------------------------------------------------------------------------- /33-MyFile.ipynb: -------------------------------------------------------------------------------- 1 | { 2 | "cells": [ 3 | { 4 | "cell_type": "code", 5 | "execution_count": 6, 6 | "metadata": {}, 7 | "outputs": [ 8 | { 9 | "name": "stdout", 10 | "output_type": "stream", 11 | "text": [ 12 | "Writing myfile.txt\n" 13 | ] 14 | } 15 | ], 16 | "source": [ 17 | "%%writefile myfile.txt\n", 18 | "Test1\n", 19 | "Test2\n", 20 | "Test3" 21 | ] 22 | }, 23 | { 24 | "cell_type": "code", 25 | "execution_count": 7, 26 | "metadata": {}, 27 | "outputs": [], 28 | "source": [ 29 | "my_file = open(\"myfile.txt\")" 30 | ] 31 | }, 32 | { 33 | "cell_type": "code", 34 | "execution_count": 8, 35 | "metadata": {}, 36 | "outputs": [ 37 | { 38 | "data": { 39 | "text/plain": [ 40 | "'Test1\\nTest2\\nTest3'" 41 | ] 42 | }, 43 | "execution_count": 8, 44 | "metadata": {}, 45 | "output_type": "execute_result" 46 | } 47 | ], 48 | "source": [ 49 | "my_file.read()" 50 | ] 51 | }, 52 | { 53 | "cell_type": "code", 54 | "execution_count": 9, 55 | "metadata": {}, 56 | "outputs": [ 57 | { 58 | "data": { 59 | "text/plain": [ 60 | "''" 61 | ] 62 | }, 63 | "execution_count": 9, 64 | "metadata": {}, 65 | "output_type": "execute_result" 66 | } 67 | ], 68 | "source": [ 69 | "my_file.read()" 70 | ] 71 | }, 72 | { 73 | "cell_type": "code", 74 | "execution_count": 10, 75 | "metadata": {}, 76 | "outputs": [ 77 | { 78 | "data": { 79 | "text/plain": [ 80 | "0" 81 | ] 82 | }, 83 | "execution_count": 10, 84 | "metadata": {}, 85 | "output_type": "execute_result" 86 | } 87 | ], 88 | "source": [ 89 | "my_file.seek(0)" 90 | ] 91 | }, 92 | { 93 | "cell_type": "code", 94 | "execution_count": 11, 95 | "metadata": {}, 96 | "outputs": [ 97 | { 98 | "data": { 99 | "text/plain": [ 100 | "'Test1\\nTest2\\nTest3'" 101 | ] 102 | }, 103 | "execution_count": 11, 104 | "metadata": {}, 105 | "output_type": "execute_result" 106 | } 107 | ], 108 | "source": [ 109 | "my_file.read()" 110 | ] 111 | }, 112 | { 113 | "cell_type": "code", 114 | "execution_count": 12, 115 | "metadata": {}, 116 | "outputs": [], 117 | "source": [ 118 | "my_file.close()" 119 | ] 120 | }, 121 | { 122 | "cell_type": "code", 123 | "execution_count": 13, 124 | "metadata": {}, 125 | "outputs": [], 126 | "source": [ 127 | "with open(\"myfile.txt\") as my_file:\n", 128 | " file_read = my_file.read()" 129 | ] 130 | }, 131 | { 132 | "cell_type": "code", 133 | "execution_count": 14, 134 | "metadata": {}, 135 | "outputs": [ 136 | { 137 | "data": { 138 | "text/plain": [ 139 | "'Test1\\nTest2\\nTest3'" 140 | ] 141 | }, 142 | "execution_count": 14, 143 | "metadata": {}, 144 | "output_type": "execute_result" 145 | } 146 | ], 147 | "source": [ 148 | "file_read" 149 | ] 150 | }, 151 | { 152 | "cell_type": "code", 153 | "execution_count": 15, 154 | "metadata": {}, 155 | "outputs": [ 156 | { 157 | "data": { 158 | "text/plain": [ 159 | "'Test1\\nTest2\\nTest3'" 160 | ] 161 | }, 162 | "execution_count": 15, 163 | "metadata": {}, 164 | "output_type": "execute_result" 165 | } 166 | ], 167 | "source": [ 168 | "file_read" 169 | ] 170 | }, 171 | { 172 | "cell_type": "code", 173 | "execution_count": 22, 174 | "metadata": {}, 175 | "outputs": [], 176 | "source": [ 177 | "with open(\"myfile.txt\",mode=\"w\") as my_new_file:\n", 178 | " my_new_file.write(\"test4\")" 179 | ] 180 | }, 181 | { 182 | "cell_type": "code", 183 | "execution_count": 23, 184 | "metadata": {}, 185 | "outputs": [ 186 | { 187 | "data": { 188 | "text/plain": [ 189 | "<_io.TextIOWrapper name='myfile.txt' mode='w' encoding='UTF-8'>" 190 | ] 191 | }, 192 | "execution_count": 23, 193 | "metadata": {}, 194 | "output_type": "execute_result" 195 | } 196 | ], 197 | "source": [ 198 | "my_new_file" 199 | ] 200 | }, 201 | { 202 | "cell_type": "code", 203 | "execution_count": 24, 204 | "metadata": {}, 205 | "outputs": [], 206 | "source": [ 207 | "with open(\"myfile.txt\",mode=\"r\") as my_new_file_2:\n", 208 | " contents = my_new_file_2.read()" 209 | ] 210 | }, 211 | { 212 | "cell_type": "code", 213 | "execution_count": 25, 214 | "metadata": {}, 215 | "outputs": [ 216 | { 217 | "data": { 218 | "text/plain": [ 219 | "'test4'" 220 | ] 221 | }, 222 | "execution_count": 25, 223 | "metadata": {}, 224 | "output_type": "execute_result" 225 | } 226 | ], 227 | "source": [ 228 | "contents" 229 | ] 230 | }, 231 | { 232 | "cell_type": "code", 233 | "execution_count": 26, 234 | "metadata": {}, 235 | "outputs": [], 236 | "source": [ 237 | "with open(\"myfile.txt\",mode=\"a\") as my_new_file_3:\n", 238 | " my_new_file_3.write(\" test 5\")" 239 | ] 240 | }, 241 | { 242 | "cell_type": "code", 243 | "execution_count": 27, 244 | "metadata": {}, 245 | "outputs": [], 246 | "source": [ 247 | "with open(\"myfile.txt\",mode=\"r\") as my_new_file_5:\n", 248 | " contents_2 = my_new_file_5.read()" 249 | ] 250 | }, 251 | { 252 | "cell_type": "code", 253 | "execution_count": 28, 254 | "metadata": {}, 255 | "outputs": [ 256 | { 257 | "data": { 258 | "text/plain": [ 259 | "'test4 test 5'" 260 | ] 261 | }, 262 | "execution_count": 28, 263 | "metadata": {}, 264 | "output_type": "execute_result" 265 | } 266 | ], 267 | "source": [ 268 | "contents_2" 269 | ] 270 | }, 271 | { 272 | "cell_type": "markdown", 273 | "metadata": {}, 274 | "source": [ 275 | "# r = read, w = write, a = append" 276 | ] 277 | }, 278 | { 279 | "cell_type": "code", 280 | "execution_count": null, 281 | "metadata": {}, 282 | "outputs": [], 283 | "source": [] 284 | } 285 | ], 286 | "metadata": { 287 | "kernelspec": { 288 | "display_name": "Python 3", 289 | "language": "python", 290 | "name": "python3" 291 | }, 292 | "language_info": { 293 | "codemirror_mode": { 294 | "name": "ipython", 295 | "version": 3 296 | }, 297 | "file_extension": ".py", 298 | "mimetype": "text/x-python", 299 | "name": "python", 300 | "nbconvert_exporter": "python", 301 | "pygments_lexer": "ipython3", 302 | "version": "3.6.4" 303 | } 304 | }, 305 | "nbformat": 4, 306 | "nbformat_minor": 2 307 | } 308 | -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | # PythonCourse 2 | This is a repository containing Udemy Python Course for Atil Samancioglu 3 | --------------------------------------------------------------------------------